From Salesforce drama to the year of generative AI
Apologies to the Grateful Dead, but what a long, strange year it’s been in 2023 enterprise tech news. It began with a ton of Salesforce drama and eventually got taken over by generative AI and ChatGPT, which seemed to come out of nowhere to completely dominate the news cycle this year.
But even though AI clearly influenced much of the news, and even my own coverage, there was still a ton of other enterprise stories that made the news this year.
The rise of generative AI in the enterprise
It would be impossible to discuss this year’s news cycle without talking about the impact of generative AI. When OpenAI released ChatGPT at the end of last year, it would have been impossible to understand the impact it would have on enterprise software in the coming months. Yet it has the potential to be truly transformative, changing the way we interact with software, and perhaps represents the biggest change to UX (user experience) design since point-and-click.
Investors have a lot to celebrate. The stock market will end 2023 near all-time highs after a fierce rebound that saw the Nasdaq Composite surge more than 40% this year, one of its best performances in decades.
It sets a high bar for 2024 as investors seek ways to continue the momentum. Three Fool.com contributors sifted through their top ideas to identify Amazon(NASDAQ: AMZN), Super Micro Computer(NASDAQ: SMCI), and SentinelOne(NYSE: S) as AI stocks with the right stuff to outperform a hot market in 2024.
Here is the investment pitch for each.
Amazon’s AI could be looking at a breakout year
Jake Lerch (Amazon): As of this writing, Amazon is up 83% year to date. It’s been an incredible year for the company, but I believe 2024 could be even better.
That’s because Amazon has only scratched the surface of its artificial intelligence (AI) potential. Indeed, in a recent interview with CNBC, CEO Andy Jassy said that “generative AI is going to change every customer experience.”
AI could prove to be an enormous competitive advantage for Amazon, which prides itself on anticipating customers’ wants and needs.
Take Alexa, Amazon’s signature virtual assistant. Jassy noted in the interview that, “if you’ve studied generative AI and you’re still scoffing, you’re really not paying attention. … We think we have a real opportunity to be the leader there, and we’re in the process of building a much more expansive large language model underneath Alexa that will make her both much more knowledgeable and much more conversational.”
In other words, get ready for a ChatGPT-like experience coming to an Alexa-enabled device near you soon. Need a new pair of shoes? Amazon wants you to talk with Alexa about the style you’re looking for, compare prices, and then buy — through an Amazon e-commerce partner, of course.
What’s more, Amazon already has a massive treasure trove for training large language models — its own data. With every search, review, or purchase, Amazon collects data that could be used to help it train and tailor its AI.
Amazon is something of a sleeping giant when it comes to AI. And 2024 could be the year that this goliath really springs to life.
The emergence of generative AI plays into the hands of this company
Will Healy(Super Micro): Super Micro Computer is not a household name for AI or tech investors. But it existed for more than 30 years and it began by selling motherboards.
Today, it’s best known for selling switches, servers, and solutions for storage and networking. However, it also offers combined hardware and software solutions that have become important amid the rise of generative AI.
Additionally, its rack-scale solutions support the cloud, metaverse, 5G, and edge infrastructure. Users may also like that Super Micro designs its products to save energy and minimize the impact on the environment. That growth helped it secure over 6 million square feet of manufacturing space and establish operations in more than 100 countries.
Thanks primarily to AI-driven interest, the AI stock is up more than 250% over the last year — outperforming powerhouse AI stocks such as Nvidia and Palantir.
SMCI Chart
There’s no guarantee Super Micro will repeat those results in 2024, and supply constraints and higher capital expenditures spending weighed on the financials. Its $2.1 billion in net sales for the first quarter of fiscal 2024 (ended Sept. 30) grew 14% yearly after revenue had surged 37% higher in fiscal 2023. Also, fiscal Q1 net income of $157 million fell short of the $184 million earned in the same year-ago quarter.
Still, with the AI-driven growth in the pipeline, that decline will probably amount to a temporary setback. The company forecasts net sales of $10 billion to $11 billion, which would mean 47% growth at the midpoint.
Moreover, Super Micro’s valuation significantly lags other AI giants despite the massive stock price gains. Its forward P/E ratio of 17 trails Nvidia’s forward earnings multiple of 40 and Palantir’s forward valuation of almost 71. That implied potential for multiple expansion and Super Micro’s positioning in the AI industry will likely mean the stock continues to march higher in 2024.
Wall Street hasn’t yet caught up to SentinelOne’s progress
Justin Pope (SentinelOne): Cybersecurity company SentinelOne went public at the height of the last bull market. The stock initially soared, then crashed as investors fled growth stocks due to rising interest rates. SentinelOne remains over 60% off its former high despite shares surging roughly 90% in 2023. But Wall Street could still be missing just how much SentinelOne progressed over these past 24 months.
The stock’s valuation peaked at a price-to-sales (P/S) ratio of over 106 but sits at just 14 today. Not only has the share price come down, but SentinelOne has been rapidly growing its business. Revenue has multiplied, and profit margins are racing higher:
S Revenue (TTM) Chart
Notably, there are plenty of opportunities for SentinelOne to keep growing and become profitable over the long term. Artificial intelligence is the foundation of its core endpoint security product and is showing up in product expansions. Its Singularity Data Lake and Cloud Security products more than doubled sales year over year in Q3, and it’s begun rolling out Purple AI, a generative AI that can assist customers in using SentinelOne’s security products.
Analysts see SentinelOne’s revenue surpassing $1 billion over the next few years. Assuming profitability continues improving as revenue grows, the stock is a prime candidate to outgrow and outrun the broader market in 2024.
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John Mackey, former CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool’s board of directors. Jake Lerch has positions in Amazon and Nvidia. Justin Pope has positions in SentinelOne. Will Healy has positions in Palantir Technologies. The Motley Fool has positions in and recommends Amazon, Nvidia, and Palantir Technologies. The Motley Fool recommends Super Micro Computer. The Motley Fool has a disclosure policy.
Marc founded Faculty to help organizations make better decisions using human-led AI. For over 10 years, he has worked with government agencies and leading brands to implement impactful AI solutions.
It’s becoming increasingly clear that businesses of all sizes and across all sectors can benefit from generative AI. From code generation and content creation to data analytics and chatbots, the possibilities are vast — and the rewards abundant.
McKinsey estimates generative AI will add $2.6 trillion to $4.4 trillion annually across numerous industries. That’s just one reason why over 80% of enterprises will be working with generative AI models, APIs, or applications by 2026. Businesses acting now to reap the rewards will thrive; those that don’t won’t remain competitive. However, simply adopting generative AI doesn’t guarantee success.
The right implementation strategy is needed. Modern business leaders must prepare for a future managing people and machines, with AI integrated into every part of their business. A long-term strategy is needed to harness generative AI’s immediate advantages while mitigating potential future risks.
Businesses that don’t address concerns around generative AI from day one risk consequences, including system failure, copyright exposure, privacy violations, and social harms like the amplification of biases. However, only 17% of businesses are addressing generative AI risks, which leaves them vulnerable.
Making good choices now will allow leaders to future-proof their business and reap the benefits of AI while boosting the bottom line.
Businesses must also ensure they are prepared for forthcoming regulations. President Biden signed an executive order to create AI safeguards, the U.K. hosted the world’s first AI Safety Summit, and the EU brought forward their own legislation. Governments across the globe are alive to the risks. C-suite leaders must be too — and that means their generative AI systems must adhere to current and future regulatory requirements.
So how do leaders balance the risks and rewards of generative AI?
Businesses that leverage three principles are poised to succeed: human-first decision-making, robust governance over large language model (LLM) content, and a universal connected AI approach. Making good choices now will allow leaders to future-proof their business and reap the benefits of AI while boosting the bottom line.
AI is all the rage — particularly text-generating AI, also known as large language models (think models along the lines of ChatGPT). In one recent survey of ~1,000 enterprise organizations, 67.2% say that they see adopting large language models (LLMs) as a top priority by early 2024.
But barriers stand in the way. According to the same survey, a lack of customization and flexibility, paired with the inability to preserve company knowledge and IP, were — and are — preventing many businesses from deploying LLMs into production.
That got Varun Vummadi and Esha Manideep Dinne thinking: What might a solution to the enterprise LLM adoption challenge look like? In search of one, they founded Giga ML, a startup building a platform that lets companies deploy LLMs on-premise — ostensibly cutting costs and preserving privacy in the process.
“Data privacy and customizing LLMs are some of the biggest challenges faced by enterprises when adopting LLMs to solve problems,” Vummadi told TechCrunch in an email interview. “Giga ML addresses both of these challenges.”
Giga ML offers its own set of LLMs, the “X1 series,” for tasks like generating code and answering common customer questions (e.g. “When can I expect my order to arrive?”). The startup claims the models, built atop Meta’s Llama 2, outperform popular LLMs on certain benchmarks, particularly the MT-Bench test set for dialogs. But it’s tough to say how X1 compares qualitatively; this reporter tried Giga ML’s online demo but ran into technical issues. (The app timed out no matter what prompt I typed.)
Even if Giga ML’s models are superior in some aspects, though, can they really make a splash in the ocean of open source, offlineLLMs?
In talking to Vummadi, I got the sense that Giga ML isn’t so much trying to create the best-performing LLMs out there but instead building tools to allow businesses to fine-tune LLMs locally without having to rely on third-party resources and platforms.
“Giga ML’s mission is to help enterprises safely and efficiently deploy LLMs on their own on-premises infrastructure or virtual private cloud,” Vummadi said. “Giga ML simplifies the process of training, fine-tuning and running LLMs by taking care of it through an easy-to-use API, eliminating any associated hassle.”
Vummadi emphasized the privacy advantages of running models offline — advantages likely to be persuasive for some businesses.
Predibase, the low-code AI dev platform, found that less than a quarter of enterprises are comfortable using commercial LLMs because of concerns over sharing sensitive or proprietary data with vendors. Nearly 77% of respondents to the survey said that they either don’t use or don’t plan to use commercial LLMs beyond prototypes in production — citing issues relating to privacy, cost and lack of customization.
“IT managers at the C-suite level find Giga ML’s offerings valuable because of the secure on-premise deployment of LLMs, customizable models tailored to their specific use case and fast inference, which ensures data compliance and maximum efficiency,” Vummadi said.
Giga ML, which has raised ~$3.74 million in VC funding to date from Nexus Venture Partners, Y Combinator, Liquid 2 Ventures, 8vdx and several others, plans in the near term to grow its two-person team and ramp up product R&D. A portion of the capital is going toward supporting Giga ML’s customer base, as well, Vummadi said, which currently includes unnamed “enterprise” companies in finance and healthcare.
NEW YORK — The New York Times has filed a federal lawsuit against OpenAI and Microsoft seeking to end the practice of using its stories to train chatbots, saying that copyright infringements at the paper alone could be worth billions.
The paper joins a growing list of individuals and publishers trying to stop OpenAI from using copyrighted material.
In the suit filed Wednesday in Manhattan federal court, the Times said OpenAI and Microsoft are advancing their technology through the “unlawful use of The Times’s work to create artificial intelligence products that compete with it” and “threatens The Times’s ability to provide that service.”
OpenAI and Microsoft did not immediately respond to requests for comment.
Media organizations have been pummeled by a migration of readers to online platforms and while many publications have carved out a digital space online as well, artificial intelligence technology has threatened to upend numerous industries, including media.
Artificial intelligence companies scrape information available online, including articles published by media organizations, to train generative AI chatbots. Those companies have attracted billions in investments very rapidly.
Microsoft has a partnership with OpenAI that allows it to capitalize on the AI technology made by the artificial intelligence company. The Redmon, Washington, tech giant is also OpenAI’s biggest backer and has invested billions of dollars into the company since the two began their partnership in 2019 with a $1 billion investment. As part of the agreement, Microsoft’s supercomputers help power OpenAI’s AI research and the tech giant integrates the startup’s technology into its products.
The number of lawsuits filed against OpenAI for copyright infringement is growing. The company has been sued by a number of writers – including comedian Sarah Silverman – who say their books were ingested to train OpenAI’s AI models without their permission. In June, more than 4,000 writers signed a letter to the CEOs of OpenAI, Google, Microsoft, Meta and other AI developers accusing them of exploitative practices in building chatbots that “mimic and regurgitate” their language, style and ideas.
The lawsuit filed Wednesday said generative AI tools developed by OpenAI and Microsoft are closely summarizing content from the Times, mimicking its style and even reciting it verbatim. The complaint cited examples of OpenAI’s GPT-4 spitting out large portions of news articles from the Times, including a Pulitzer-Prize winning investigation into New York City’s taxi industry that was published in 2019 and took 18 months to complete. It also cited outputs from Bing Chat that it said included verbatim excerpts from Times articles.
The Times did not list specific damages that it is seeking, but said the legal action “seeks to hold them responsible for the billions of dollars in statutory and actual damages that they owe for the unlawful copying and use of The Times’s uniquely valuable works.”
The Times, however, is seeking the destruction of GPT and other large language models or training sets that incorporate its work.
In the complaint, the Times said Microsoft and OpenAI “seek to free-ride on The Times’s massive investments in its journalism” by using it to build products without payment or permission.
In July, OpenAI and The Associated Press announced a deal for the artificial intelligence company to license AP’s archive of news stories.
The New York Times said it’s never given permission to anyone to use its content for generative AI purposes.
The lawsuit also follows what appears to be breakdowns in talks between the newspaper and the two companies.
The Times said it reached out to Microsoft and OpenAI in April to raise concerns about the use of its intellectual property and reach a resolution on the issue. During the talks, the newspaper said it sought to “ensure it received fair value” for the use of its content, “facilitate the continuation of a healthy news ecosystem, and help develop GenAI technology in a responsible way that benefits society and supports a well-informed public.”
“These negotiations have not led to a resolution,” the lawsuit said.
NEW YORK — The New York Times has filed a federal lawsuit against OpenAI and Microsoft seeking to end the practice of using its stories to train chatbots, saying that copyright infringements at the paper alone could be worth billions.
The paper joins a growing list of individuals and publishers trying to stop OpenAI from using copyrighted material.
In the suit filed Wednesday in Manhattan federal court, the Times said OpenAI and Microsoft are advancing their technology through the “unlawful use of The Times’s work to create artificial intelligence products that compete with it” and “threatens The Times’s ability to provide that service.”
OpenAI and Microsoft did not immediately respond to requests for comment.
Media organizations have been pummeled by a migration of readers to online platforms and while many publications have carved out a digital space online as well, artificial intelligence technology has threatened to upend numerous industries, including media.
Artificial intelligence companies scrape information available online, including articles published by media organizations, to train generative AI chatbots. Those companies have attracted billions in investments very rapidly.
Microsoft has a partnership with OpenAI that allows it to capitalize on the AI technology made by the artificial intelligence company. The Redmon, Washington, tech giant is also OpenAI’s biggest backer and has invested billions of dollars into the company since the two began their partnership in 2019 with a $1 billion investment. As part of the agreement, Microsoft’s supercomputers help power OpenAI’s AI research and the tech giant integrates the startup’s technology into its products.
The number of lawsuits filed against OpenAI for copyright infringement is growing. The company has been sued by a number of writers – including comedian Sarah Silverman – who say their books were ingested to train OpenAI’s AI models without their permission. In June, more than 4,000 writers signed a letter to the CEOs of OpenAI, Google, Microsoft, Meta and other AI developers accusing them of exploitative practices in building chatbots that “mimic and regurgitate” their language, style and ideas.
The lawsuit filed Wednesday said generative AI tools developed by OpenAI and Microsoft are closely summarizing content from the Times, mimicking its style and even reciting it verbatim. The complaint cited examples of OpenAI’s GPT-4 spitting out large portions of news articles from the Times, including a Pulitzer-Prize winning investigation into New York City’s taxi industry that was published in 2019 and took 18 months to complete. It also cited outputs from Bing Chat that it said included verbatim excerpts from Times articles.
The Times did not list specific damages that it is seeking, but said the legal action “seeks to hold them responsible for the billions of dollars in statutory and actual damages that they owe for the unlawful copying and use of The Times’s uniquely valuable works.”
The Times, however, is seeking the destruction of GPT and other large language models or training sets that incorporate its work.
In the complaint, the Times said Microsoft and OpenAI “seek to free-ride on The Times’s massive investments in its journalism” by using it to build products without payment or permission.
In July, OpenAI and The Associated Press announced a deal for the artificial intelligence company to license AP’s archive of news stories.
The New York Times said it’s never given permission to anyone to use its content for generative AI purposes.
The lawsuit also follows what appears to be breakdowns in talks between the newspaper and the two companies.
The Times said it reached out to Microsoft and OpenAI in April to raise concerns about the use of its intellectual property and reach a resolution on the issue. During the talks, the newspaper said it sought to “ensure it received fair value” for the use of its content, “facilitate the continuation of a healthy news ecosystem, and help develop GenAI technology in a responsible way that benefits society and supports a well-informed public.”
“These negotiations have not led to a resolution,” the lawsuit said.
Many have dubbed 2023 the year of AI, as the pace of artificial intelligence breakthroughs this year has been fast — and for some, concerning.
However, fear didn’t stop people from jumping on the AI bandwagon, a new study confirms. With more than 14 billion visits between September 2022 and August 2023, ChatGPT is the most popular generative AI tool in the world, according to a new survey from Writerbuddy.ai, an online content writing company.
Writerbuddy analyzed over 3,000 artificial intelligence tools using SEMrush, a popular SEO software, to determine the most used tools of the year. Altogether, the top 50 AI tools attracted over 24 billion visits, most of which came from male users.
Here are the top 10 most popular AI tools, according to the rankings:
1. ChatGPT
Tool category: AI Chatbot
Total visits: 14.6B
2. Character.ai
Tool category: AI Chatbot
Total visits: 3.8B
3. Quillbot
Tool category: AI Writing
Total visits: 1.1B
4. Midjourney
Tool category: Image Generator
Total visits: 500.4M
5. Hugging Face
Tool category: Data Science
Total visits: 316.6M
6. Bard
Tool category: AI Chatbot
Total visits: 241.6M
7. NovelAI
Tool category: AI Writing
Total visits: 238.7M
8. Capcut
Tool Category: Video Generator
Total visits: 203.8M
9. Janitor AI
Tool category: AI Chatbot
Total visits: 192.4M
10. Civitai
Tool category: Image Generator
Total visits: 177.2M
ChatGPT has earned some negative press this year — from Sam Altman’s leadership shakeup to potentially harmful AI developments — but people keep using the generative tool. The industry leading bot can carry out an array of tasks, from planning out your weekly schedule to writing you a detailed resume.
Other generative tools on the list, like Google’s Bard and Quillbot, have similar capabilities as they can summarize and paraphrase text, but haven’t yet garnered the same popularity as Open AI’s chatbot. And tools like Character.ai and Novel.ai are used by many as virtual companions.
If you’re only using AI for entertainment purposes, you may be missing out on the opportunity to make money without a fancy job or college degree, according to Susan Gonzales, founder and CEO of AIandYou, a nonprofit that teaches AI skills to people from marginalized communities.
Say you’re a freelancer or a small business owner. AI tools can “help improve [your] business, improve inventory management, analyze customer behavior or gain competitive intelligence,” Gonzales told CNBC Make It in July. “Small businesses can use AI tools to target their marketing and advertising efforts more effectively … They can identify new revenue opportunities.”
And if you’re looking for a side gig, like tutoring, AI can help you do that, too.
“There are many online learning opportunities to understand how AI works, which then could help [someone] possibly become an AI tutor, or to do some AI training to pass it on to the next generation,” Gonzales said. “The wonderful thing today is … all the information is out there.”
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Three years ago, data analytics company Palantir(NYSE: PLTR) debuted on public markets through a direct listing. Since then, its shares have risen around 80%, with most of that growth coming from a recovery in 2023 as investors became more optimistic in its ability to incorporate new generative artificial intelligence (AI) tech into its business model. Let’s explore what the next 10 years could have in store for the company.
Palantir’s unique take on machine learning
Palantir is an American software company known for data fusion and mining, a process that involves analyzing a large volume of information and combining data from different sources into useful insights. The company is unique because of its significant exposure to sensitive government clients and missions.
According to CNBC, Palantir’s software helped the U.S. find Osama Bin Laden in 2011. And it is currently used to help the Ukrainian armed forces with targeting in the war with Russia.
So far, Palantir’s business is performing reasonably well. Third-quarter earnings grew 17% year over year to $558 million, with the fastest growth coming from its commercial clients, which increased 23% to $251 million — a bit under half of the total. Public sector deals represented the rest.
While Palantir’s government contracts give its business stability and a solid niche (not every company is trusted to deal with such classified and sensitive information), commercial clients could represent a significant potential growth opportunity in the future. Management is rapidly incorporating generative AI into its business model to make its software solutions more useful to potential enterprise clients.
AI will become a bigger part of the business
Generative AI is a unique subfield of artificial intelligence where algorithms are designed to create new content based on vast arrays of training data. While this is distinct from Palantir’s legacy data management businesses, the two technologies synergize well. For example, generative AI could help automate Palantir’s analytics process or give clients real-time conversational insights about their data in fast-paced scenarios like battlefields or law enforcement operations.
Image source: Getty Images.
In April, Palantir launched its new Artificial Intelligence Platform (AIP), designed to add AI to its existing software offerings like Gotham, which is for government uses, and Foundry, geared toward the private sector.
Bloomberg Intelligence expects the total generative AI market to be worth a jaw-dropping $1.3 trillion by 2032, with a significant portion of the opportunity coming from software. Over the next 10 years, investors can expect Palantir’s AI efforts to become a key growth driver as the technology improves and more organizations implement it into their operations. Palantir’s public sector relationships and existing data mining business could give it an edge against potential rivals that may emerge.
Palantir can justify its valuation
Valuation will also be a big concern for long-term Palantir investors. With a forward price-to-earnings multiple of 61, the company trades at a substantial premium to the S&P 500‘s average of 26. But the price looks somewhat justified by the company’s solid bottom-line momentum.
Third-quarter net income jumped from a loss of $123.9 million to a gain of $80 million, capping off Palantir’s first four consecutive quarters of profitability under generally accepted accounting principles (GAAP). The company’s burgeoning profitability and cash flow could give it a stable foundation for its AI expansion over the coming years. And shares look capable of outperforming the market.
Should you invest $1,000 in Palantir Technologies right now?
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Artificial intelligence is expected to reshape the wealth management industry — and those who don’t embrace the technology are at risk of falling behind, experts believe. Those in the younger, digitally native generation are now aging and growing their wealth. They expect more digitization and personalization, so wealth management firms are turning to AI to meet those needs, William Blair analyst Jeff Schmitt said in an Oct. 20 note. Despite early skepticism, advisors now realize that AI can be an effective tool in improving their practices and augment — not replace — human interaction, he said. “Wealth managers that are adapting to this changing landscape by implementing and scaling AI technologies are best positioned to capitalize on these demographic trends and should see greater market share gains and profitability in the coming years,” he wrote. Artificial intelligence has been around for several years already within wealth management, with advisors using technology such as machine learning and natural language processing to help analyze data, said Roland Kastoun, U.S. asset and wealth management consulting leader for PwC. Now, that technology combined with generative AI can really help grow productivity and revenue, he said. Already big names such as Morgan Stanley , BlackRock and JPMorgan have all implemented generative AI solutions . “There are going to be opportunities to invest that don’t currently exist,” said Wells Fargo analyst Mike Mayo. “There is one out in the top of the first inning and it is hard to say exactly who wins.” However, on a broad scale he sees JPMorgan as the clear frontrunner right now. “JPMorgan does seem to have the digitization, the data, and the maturity of processes to deploy AI in ways that many others cannot,” Mayo said. They also can attract more talent, which will be key, he added. JPM YTD mountain JPMorgan year to date Meanwhile, Charles Schwab is Schmitt’s top pick for 2024. While he believes the stock is well positioned to outperform due to the potential for a significant earnings rebound, he is also bullish on Schwab’s AI capabilities. The wealth management firm is the largest, with $8 trillion in client assets, and has been using its scale and technology to build artificial intelligence focusing on improving customer service, Schmitt wrote in his note. “While Schwab continues to build out core AI capabilities, we believe this will accelerate over time as it looks to remain an industry leader in customer service levels and pricing,” he said. Among the other names Schmitt also has overweight ratings on are Morgan Stanley, Ameriprise Financial and Envestnet . In September, Morgan Stanley unveiled its generative AI assistant for financial advisors to help “revolutionize” client interactions and bring new efficiencies, the firm said in a memo to staff. Envestnet, the largest provider of wealth-tech solutions for advisors in the U.S., is in the early stages of AI adoption, but has the resources to continue enhancing and scaling its AI capabilities, Schmitt said. Meanwhile, wealth-management company Ameriprise has been working on its AI software over the last few years to streamline operations, augment advisor productivity and boost customer service, Schmitt added. Veteran tech investor Paul Meeks particularly likes BlackRock, which he thinks will benefit as AI pushes more investors into passive investing over active. State Street, Invesco and Schwab can also benefit from that continued shift, he said. The larger institutions, such as Morgan Stanley and Goldman Sachs , will also leverage the technology, said Meeks, a professor at the Baker School of Business at The Citadel. “AI can be used for not only creating an asset allocation for a client and maybe even driving some security selection but also for their marketing,” he said. AI can very inexpensively and efficiently reach a much larger audience, he added. He’s not necessarily jumping into bank stocks right now, however. “When interest rates start to fall, we will get a double whammy — the benefit from the AI trend and the benefit from falling rates,” he said. — CNBC’s Michael Bloom contributed reporting.
Like it or not, generative artificial intelligence has arrived on Wall Street — and experts expect it to transform the way firms do business.
To be clear, artificial intelligence, like natural language processing and machine learning, has been used by wealth management and asset management firms for years. Yet with generative AI now on the scene, it can have a powerful impact when combined with other AI technologies, said Roland Kastoun, U.S. asset and wealth management consulting leader for PwC.
“We see this as a massive accelerator of productivity and revenue growth for the industry,” he said.
In fact, the banking sector is expected to have one of the largest opportunities in generative AI, according to McKinsey & Company. Gen AI could add the equivalent of $2.6 trillion to $4.4 trillion annually in value across the 63 use cases the McKinsey Global Institute analyzed. While not the largest beneficiaries within banking, asset management could see $59 billion in value and wealth management could see $45 billion.
Some of the biggest names in the business are already on board.
Earlier this month, BlackRock sent a memo to employees that in January it will roll out to its clients generative AI tools for Aladdin and eFront to help users “solve simple how-to questions,” the memo said.
“GenAI will change how people interact with technology. It will improve our productivity and enhance the great work we are already doing. GenAI will also likely change our clients’ expectations around the frequency, timeliness, and simplicity of our interactions,” the memo said.
Meanwhile, Morgan Stanley unveiled its generative AI assistant for financial advisors, called AI @ Morgan Stanley Assistant, in September. The firm’s co-President Andy Saperstein said in a memo to staffers that generative AI will “revolutionize client interactions, bring new efficiencies to advisor practices, and ultimately help free up time to do what you do best: serve your clients.”
Earlier this year, both JPMorgan and Goldman Sachs said they were developing ChatGPT-style AI in house. JPMorgan’s IndexGPT will tap “cloud computing software using artificial intelligence” for “analyzing and selecting securities tailored to customer needs,” according to a filing in May. Goldman said its technology will help generate and test code.
Those who don’t embrace AI will be left behind, said Wells Fargo bank analyst Mike Mayo.
“If the bank across the street has financial advisors that are using AI, how can you not be using it too?” he said. “It certainly increases the stakes for competition, and you can keep up or fall behind.”
In fact, as the younger generation ages, those digitally native investors will seek greater digitization, more personalized solutions and lower fees, William Blair analyst Jeff Schmitt said in an Oct. 20 note.
“Given that these investors will control an increasing share of invested assets over time, wealth management firms and advisors are leveraging AI to enhance offerings and adjust service delivery models to win them over,” he wrote.
Cerulli Associates estimated some $72.6 trillion in wealth will be transferred to heirs through 2045.
The big appeal of generative AI — and a differentiator from other AI tech — is its ability to generate content, said PwC’s Kastoun.
It’s one thing for technology to analyze a large set of content, he pointed out. “It’s another thing for it to be able to generate new content based on the data that it has, and that’s what’s creating a lot of hype.”
Yet what he’s seeing in both the wealth management and asset management business is the use of multiple elements of AI, not just generative AI, he said.
“It’s the power of combining these different technologies and methodologies that is really creating an impact across the industry,” Kastoun said.
Firms are now figuring out how to incorporate generative AI into their businesses and existing AI technologies. At T. Rowe Price, its New York City Technology Development Center has been building AI capabilities for several years.
“We ultimately are looking to help our decision makers get the benefit of data and insights to do their job better,” said Jordan Vinarub, head of the center.
His team made a big pivot with the arrival of generative AI.
“We kind of saw this as an existential moment for the firm to say, we need to understand this and figure out how we can use it to support the business,” Vinarub said. “Over the past, I guess, six months … we’ve gone from just pure research and proofs of concept to then building our own internal application on top of the large language model to help assist our investors and research process.”
It’s not only the big firms adapting to generative AI; smaller upstarts are looking for ways to disrupt the industry.
Wealth-tech firm Farther is one of those. Its co-founder, Brad Genser, said the company is a “new type of financial institution” that was built to combine expert advisors and AI.
“If you don’t build the technology, along with the human processes, and you don’t control both, you end up with something that’s incomplete,” he said. “If you do it together, you’re building people processes and technology together, then you get something that’s greater than the sum of its parts.”
Then there is Magnifi, an investing platform that uses ChatGPT and computer programs to give personal investing advice. Investors link the technology to their various accounts, and Magnifi can monitor their portfolios. About 45,000 subscribers have connected over $500 million in aggregate assets to the platform, Magnifi said in November.
“It’s a copilot alongside individual consumers that they’re interacting with over time,” said Tom Van Horn, Magnifi’s chief operating and product officer. “It’s not taking over control, it’s empowering those individuals to get to better wealth outcomes.”
The technology is so fast moving, it’s difficult to know what use cases could exist in the future. Yet certainly as productivity continues to increase, advisors can increase their time and level of engagement with their clients.
“It could change the way we think about a lot of the way we set up our business models,” PwC’s Kastoun said.
It’s also about people working with the technology and not the technology necessarily replacing humans, experts said.
“The dream state is that every employee will have an AI copilot or AI coworker and that each customer will have the equivalent of an AI agent,” Wells Fargo’s Mayo said. “I’m not talking about computers alone. I’m not talking about humans alone, but humans plus AI can compete better than either computers or humans alone.”
— CNBC’s Michael Bloom contributed reporting.
Correction: This article has been updated to reflect that Magnifi said in November that about 45,000 subscribers have connected over $500 million in aggregate assets to the platform. A previous version misstated the amount of assets.
Are there signs this prediction is already becoming true? Headline numbers can make that seem so.
According to a recent report of 750 business leaders using AI from ResumeBuilder, 37% say the technology replaced workers in 2023. Meanwhile, 44% report that there will be layoffs in 2024 resulting from AI efficiency.
But even amid reports of AI-inspired layoffs, many experts disagree with Musk’s view.
Julia Toothacre, resume and career strategist at ResumeBuilder, recognizes the numbers from its research may not accurately reflect the broad business landscape. “There are still so many traditional organizations and small businesses that do not embrace technology the way that some of the larger companies do,” Toothacre said.
Layoffs are a reality, but AI technology is also enabling business leaders to restructure and redefine the jobs we do.
Alex Hood, chief product officer at project management and collaboration software company Asana, estimates that half the time we spend at work is on what he calls “work about work.” Here, he’s referring to the status updates, cross-departmental communication and all the other parts of work that aren’t at the core of why we’re there.
“If that can be reduced because of AI, that can be a great unlock,” said Hood.
He says that without the nuance behind the numbers, the statistics marking and predicting AI-induced layoffs reflect fear more than reality.
With AI tackling task-based work, humans have the opportunity to move up the value chain, says Marc Cenedella, founder of Leet Resumes and Ladders. “For the entire economy,” Cenedella said workers will be able to focus on “integrating or structuring or defining what the task-based work is.” He compares this shift to mid-century office culture, when there were entire floors of typists — something that the efficiency of word processors eliminated.
White-collar work and ‘human-centered’ AI
According to Asana’s State of AI at Work 2023 report, employees say that 29% of their work tasks are replaceable by AI. However, Asana is a proponent of what it calls “human-centered AI,” which seeks to enhance human abilities and collaboration, not replace people outright. The more people understand human-centered AI, the more they believe it will have a positive impact on their work, the report states.
White-collar and clerical workers represent somewhere between 19.6%–30.4% of all employed people globally, according to the United Nations. Analytical and communication tools have redirected knowledge work over the years, and “generative AI should be considered another development in this long continuum of change.”
But as of 2022, 34% of the global population still did not have access to the internet, so any conversation around AI’s impact on layoffs and potential restructuring of the work needs to also include discussion of a wider mote between the technological haves and have-nots.
A worker’s personal responsibility and AI tinkering
For professionals seeking to avoid redundancy in an AI-fueled work environment, there are steps to take.
Cenedella says that being a modern white-collar professional bears a level of personal responsibility. “Part of your job is to keep developing new skills,” he said. “If you learned some software five years ago, that’s not enough. You’ve got to learn new software today.”
While positions like research and data analysis are in line for AI automation, for example, companies will still need someone to prompt the AI, make sense of the results and take action.
“My advice for anyone is to understand how AI could impact your position in your industry right now,” Toothacre said. “At least you have an idea of what to potentially expect versus having no idea what’s going on.”
But Cenedella also recognizes that there’s an expectation for business leaders to help employees continue developing their skills during their time at the company. “Just out of their own self-interest, the companies that do fund the development of their employees are going to be better positioned to be a little bit more ahead of the companies that don’t,” he said.
Even Hood, who’s on the front lines of creating collaboration and project management solutions using AI, still experiments with his own products. In preparation for an upcoming performance review for a member of his team, Hood experimented by asking AI to summarize how he was collaborating with the team member.
The AI produced a list of all of their shared interests, all of the assignments and feedback between them, and a characterization of their relationship based on messages they’ve sent to each other. In this, Hood exemplifies what AI tinkering can look like.
“You learn it by asking it questions and seeing what it’s capable of, and in some ways being disappointed, and in some ways being wowed, and then leaning into that,” Hood said. “The best thing that employers can do is give folks the ability to understand what the art of the possible is through individual experimentation using AI today.”
While layoffs are happening as a result of the current generation of AI, there’s no historical evidence that technological advancements such as this will result in mass unemployment. The workforce has a history of malleability, and increased technological capacity can result in “higher value” work, as Cenedella says — and more productivity that future generations of AI will likely learn to handle.
Sure, there’s a lot of hype surrounding artificial intelligence (AI). It always happens with hot technologies. But don’t think for a second that AI is only a fad. The advances we’ve seen over the last year or so are just the beginning.
As a result, investors still have a tremendous opportunity to make money in the coming years. Here are three unstoppable AI stocks to buy and hold for the next decade (listed in alphabetical order).
1. Alphabet
Anyone who thought that Alphabet(NASDAQ: GOOG)(NASDAQ: GOOGL) would be left in the dust in the AI race is probably rethinking that position now. Admittedly, the company appeared to be blindsided by the early success of OpenAI’s ChatGPT. And Google Cloud’s less-than-impressive growth in the third quarter was widely chalked up to a perceived AI shortcoming.
However, Alphabet seems to have changed the narrative quite a bit with the introduction of its new Gemini AI model. The most powerful version of the model, Gemini Ultra, outperforms OpenAI’s GPT-4 and beats human experts on the MMLU (massive multitask language understanding) test.
I think that Google Cloud will return to its previous growth trajectory, thanks to Gemini. Even if that’s overly optimistic, the company’s cloud platform should have huge growth prospects as customers flock to the cloud to build generative AI apps.
What about the possibility that Alphabet’s search business could be disrupted by AI? I predict that it will — but not in the way that some envision. My view is that search won’t be replaced by AI. Instead, I expect that Google’s use of AI will enhance its search functionality and make it more profitable.
2. Amazon
Amazon(NASDAQ: AMZN) was another AI leader that appeared to have been initially caught off guard by ChatGPT’s popularity. Like Alphabet, though, the e-commerce and cloud services giant quickly rolled out its own generative AI capabilities.
My take is that Amazon is on the right track with Amazon Bedrock. This service allows Amazon Web Services (AWS) customers to quickly build generative AI apps with a range of tools at their disposal.
I’m also in full agreement with Amazon CEO Andy Jassy about the long-term potential for AWS because of AI. Jassy said in the company’s Q3 conference call, “[C]ustomers want to bring the [AI] models to their data, not the other way around. And most of that data resides in AWS as the clear market segment leader in cloud infrastructure.”
Investors have definitely noticed Amazon’s renewed focus on increasing profitability. I anticipate that those profits will continue to grow robustly for years to come as the company harnesses the power of AI across all of its businesses.
3. Microsoft
My inclusion of Alphabet and Amazon among the unstoppable AI stocks to buy and hold doesn’t mean that I think they’ll grow at the expense of Microsoft(NASDAQ: MSFT). That’s not the case at all. I believe that Microsoft will remain one of the biggest AI winners for a long time to come.
Microsoft’s significant investment in OpenAI could go down as one of the smartest business development moves in corporate history. The two companies are now joined at the hip. And it shows with OpenAI’s GPT-4 technology integrated throughout Microsoft’s products.
I’m not concerned about the recent soap opera with the firing and prompt rehiring of Sam Altman as OpenAI’s CEO. OpenAI — and Microsoft, by extension — will almost certainly continue to pioneer AI breakthroughs.
Like Alphabet and Amazon, Microsoft is poised to profit tremendously as customers move their apps and data to the cloud. AI should also help the Seattle-based tech giant in many other ways, including attracting more customers to its AI-enhanced productivity tools.
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Artificial intelligence went mainstream in 2023 — it was a long time coming yet has a long way to go for the technology to match people’s science fiction fantasies of human-like machines.
Catalyzing a year of AI fanfare was ChatGPT. The chatbot gave the world a glimpse of recent advances in computer science even if not everyone figured out quite how it works or what to do with it.
“I would call this an inflection moment,” pioneering AI scientist Fei-Fei Li said. “2023 is, in history, hopefully going to be remembered for the profound changes of the technology as well as the public awakening. It also shows how messy this technology is.”
It was a year for people to figure out “what this is, how to use it, what’s the impact — all the good, the bad and the ugly,” she said.
The first AI panic of 2023 set in soon after New Year’s Day when classrooms reopened and schools from Seattle to Paris started blocking ChatGPT. Teenagers were already asking the chatbot — released in late 2022 — to compose essays and answer take-home tests.
AI large language models behind technology such as ChatGPT work by repeatedly guessing the next word in a sentence after having “learned” the patterns of a huge trove of human-written works. They often get facts wrong. But the outputs appeared so natural that it sparked curiosity about the next AI advances and its potential use for trickery and deception.
Worries escalated as this new cohort of generative AI tools — spitting out not just words but novel images, music and synthetic voices — threatened the livelihoods of anyone who writes, draws, strums or codes for a living. It fueled strikes by Hollywood writers and actors and legal challenges from visual artists and bestselling authors.
Some of the AI field’s most esteemed scientists warned that the technology’s unchecked progress was marching toward outsmarting humans and possibly threatening their existence, while other scientists called their concerns overblown or brought attention to more immediate risks.
By spring, AI-generated deepfakes — some more convincing than others — had leaped into U.S. election campaigns, where one falsely showed Donald Trump embracing the nation’s former top infectious disease expert. The technology made it increasingly difficult to distinguish between real and fabricated war footage in Ukraine and Gaza.
By the end of the year, the AI crises had shifted to ChatGPT’s own maker, the San Francisco startup OpenAI, nearly destroyed by corporate turmoil over its charismatic CEO, and to a government meeting room in Belgium, where exhausted political leaders from across the European Union emerged after days of intense talks with a deal for the world’s first major AI legal safeguards.
The new AI law won’t take effect until 2025, and other lawmaking bodies — including the U.S. Congress — are still a long way from enacting their own.
There’s no question that commercial AI products unveiled in 2023 incorporated technological achievements not possible in earlier stages of AI research, which trace back to the mid-20th century.
But the latest generative AI trend is at peak hype, according to the market research firm Gartner, which has tracked what it calls the “hype cycle” of emerging technology since the 1990s. Picture a wooden rollercoaster ticking up to its highest hill, about to careen down into what Gartner describes as a “trough of disillusionment” before coasting back to reality.
“Generative AI is right in the peak of inflated expectations,” Gartner analyst Dave Micko said. “There’s massive claims by vendors and producers of generative AI around its capabilities, its ability to deliver those capabilities.”
Google drew criticism this month for editing a video demonstration of its most capable AI model, called Gemini, in a way that made it appear more impressive — and human-like.
Micko said leading AI developers are pushing certain ways of applying the latest technology, most of which correspond to their current line of products — be they search engines or workplace productivity software. That doesn’t mean that’s how the world will use it.
“As much as Google and Microsoft and Amazon and Apple would love us to adopt the way that they think about their technology and that they deliver that technology, I think adoption actually comes from the bottom up,” he said.
It’s easy to forget that this isn’t the first wave of AI commercialization. Computer vision techniques developed by Li and other scientists helped sort through a huge database of photos to recognize objects and individual faces and help guide self-driving cars. Speech recognition advances made voice assistants like Siri and Alexa a fixture in many people’s lives.
“When we launched Siri in 2011, it was at that point the fastest-growing consumer app and the only major mainstream application of AI that people had ever experienced,” said Tom Gruber, co-founder of Siri Inc., which Apple bought and made an integral iPhone feature.
But Gruber believes what’s happening now is the “biggest wave ever” in AI, unleashing new possibilities as well as dangers.
“We’re surprised that we could accidentally encounter this astonishing ability with language, by training a machine to play solitaire on all of the internet,” Gruber said. “It’s kind of amazing.”
The dangers could come fast in 2024, as major national elections in the U.S., India and elsewhere could get flooded with AI-generated deepfakes.
In the longer term, AI technology’s rapidly improving language, visual perception and step-by-step planning capabilities could supercharge the vision of a digital assistant — but only if granted access to the “inner loop of our digital life stream,” Gruber said.
“They can manage your attention as in, ‘You should watch this video. You should read this book. You should respond to this person’s communication,’” Gruber said. “That is what a real executive assistant does. And we could have that, but with a really big risk of personal information and privacy.”
ROME — Pope Francis on Thursday called for an international treaty to ensure artificial intelligence is developed and used ethically, arguing that the risks of technology lacking human values of compassion, mercy, morality and forgiveness are too great.
Francis added his voice to increasing calls for binding, global regulation of AI in his annual message for the World Day of Peace, which the Catholic Church celebrates each Jan. 1. The Vatican released the text of the message on Thursday.
For Francis, the appeal is somewhat personal: Earlier this year, an AI-generated image of him wearing a luxury white puffer jacket went viral, showing just how quickly realistic deepfake imagery can spread online.
The pope’s message was released just days after European Union negotiators secured provisional approval on the world’s first comprehensive AI rules that are expected to serve as a gold standard for governments considering their own regulation.
Artificial intelligence has captured world attention over the past year thanks to breathtaking advances by cutting-edge systems like OpenAI’s ChatGPT that have dazzled users with the ability to produce human-like text, photos and songs. But the technology has also raised fears about the risks the rapidly developing technology poses to jobs, privacy and copyright protection and even human life itself.
Francis acknowledged the promise AI offers and praised technological advances as a manifestation of the creativity of human intelligence, echoing the message the Vatican delivered at this year’s U.N. General Assembly where a host of world leaders raised the promise and perils of the technology.
But his new peace message went further and emphasized the grave, existential concerns that have been raised by ethicists and human rights advocates about the technology that promises to transform everyday life in ways that can disrupt everything from democratic elections to art.
He insisted that the technological development and deployment of AI must keep foremost concerns about guaranteeing fundamental human rights, promoting peace and guarding against disinformation, discrimination and distortion.
His greatest alarm was devoted to the use of AI in the armaments sector, which has been a frequent focus of the Jesuit pope who has called even traditional weapons makers “merchants of death.”
He noted that remote weapons systems had already led to a “distancing from the immense tragedy of war and a lessened perception of the devastation caused by those weapons systems and the burden of responsibility for their use.”
“The unique capacity for moral judgment and ethical decision-making is more than a complex collection of algorithms, and that capacity cannot be reduced to programming a machine,” he wrote.
He called for “adequate, meaningful and consistent” human oversight of Lethal Autonomous Weapons Systems (or LAWS), arguing that the world has no need for new technologies that merely “end up promoting the folly of war.”
On a more basic level, he warned about the profound repercussions on humanity of automated systems that rank citizens or categorize them. He noted that such technology could determine the reliability of an applicant for a mortgage, the right of a migrant to receive political asylum or the chance of reoffending by someone previously convicted of a crime.
“Algorithms must not be allowed to determine how we understand human rights, to set aside the essential human values of compassion, mercy and forgiveness, or to eliminate the possibility of an individual changing and leaving his or her past behind,” he wrote.
For Francis, the issue hits at some of his priorities as pope to denounce social injustices, advocate for migrants and minister to prisoners and those on the margins of society.
The pope’s message didn’t delve into details of a possible binding treaty other than to say it must be negotiated at a global level, to both promote best practices and prevent harmful ones. Technology companies alone cannot be trusted to regulate themselves, he said.
He repurposed arguments he has used before to denounce multinationals that have ravaged Earth’s national resources and impoverished the Indigenous peoples who live off them.
Freedom and peaceful coexistence are threatened “whenever human beings yield to the temptation to selfishness, self-interest, the desire for profit and the thirst for power,” he wrote.
Instagram introduced its generative AI-powered background editing tool to U.S.-based users Wednesday.
Meta’s lead for generative AI Ahmad Al-Dahle posted on Threads saying that the tool will let users change the background to their images through prompts for Stories.
When users will tap on the background editor icon on an image they will get ready prompts like “On a red carpet,” “Being chased by dinosaurs,” and “Surrounded by puppies.” Users can write their own prompts to change the background as well.
Once a user posts a Story with the newly generated background, others will see a “Try it” sticker with the prompt so they can also play with the image generation tool.
Instagram’s AI-powered background editor is available for U.S-based users Image Credits: Instagram
Earlier in the month, Meta made its 28 AI-powered characters available across all its apps — WhatsApp, Messenger, and Instagram — for U.S.-based users with support for Bing search and better context window. At the same time, the company also launched a standalone AI-image generator called Imagine with Meta, powered by its own model called Emu.
Opinions expressed by Entrepreneur contributors are their own.
A little over four years ago, I was collaborating on a project with a colleague who happened to be working on his Ph.D. in artificial intelligence. Our client was in the online education space and looking to build a program that could examine a student’s history of learning and recommend what they should study next.
The request was straightforward. The challenge was the data the client wanted to collect was in an array of formats: There was information from their online system, but also papers and exams, all of which were graded differently. While one might have been marked with a percentage or grade, another could have two check marks or a smiley face.
As I tried to wrap my head around how we would evaluate the difference between a letter grade and an emoji, my colleague assured me AI could do that part for us.
That was when my perception of AI changed. Up until then, I thought of AI as smart algorithms, capable of taking a set of data and boiling it down to an answer. I was blown away that it had evolved to take in unstructured information and cross-reference it against sources to generate recommendations.
Fast forward to today and generative AI is sweeping through the business landscape faster than any technology we’ve seen to date — OpenAI’s ChatGPT has become the fastest-growing consumer application in history. Startups and big tech alike are leveraging it to build new business models and drastically scale operations.
Recently, I heard a speaker on a 50-city tour compare generative AI’s impact on the business world to an asteroid headed for every company that doesn’t embrace it. I like to think a little more optimistically. While there’s no denying AI is poised to drastically change business as we know it, I believe it has the potential to be the best or worst thing that happens to your company. Here’s how to make the most of the opportunity.
A lot of the CEOs and senior leaders I work with understand AI at a high level, but they’re taking a conservative wait-and-see approach. They want more case studies or feel it’s too early to make investments in the technology.
This is a logical approach. I understand not wanting to pay the premium that early adopters incur when they invest in a new technology; not only can there be bugs and defects in early models, but you don’t benefit from new features often included in successive iterations as the tech evolves.
When it comes to generative AI, however, there’s a lot of upside to understanding how the technology can transform your business early on. From improved customer insights to more cost-effective and scalable service delivery, early adopters of AI are quickly realizing the competitive advantage it offers. A recent survey from Salesforce showed that 67% of IT leaders have prioritized generative AI for their businesses in the next 18 months.
For those who are hesitant, a great place to start is to identify one high-cost area of your business that could be made more efficient through an investment in AI. For example, we recently engaged in a project for a large enterprise that’s spending a significant portion of its marketing budget on language translation services. Leveraging AI to build the language technology in-house is a one-time investment that will cost them half of what they’re spending on outsourcing. Not only that, but the in-house solution removes internal processes and drastically improves the speed of translation.
By tackling one tangible business problem through AI, not only can you realize significant cost savings, but you can also start to understand its capabilities and visualize how it can transform other areas of your business.
From Microsoft’s $13 billion bet on OpenAI to Amazon’s recent $4 billion investment in AI startup Anthropic, the race to capitalize on the business opportunities AI presents is on, and it’s not just big tech getting into the game — AI’s share of U.S. startup funding doubled in 2023, with more than 1 in 4 dollars invested in American startups going to AI-related companies.
These investments aren’t just driven by the desire for improved ROI or cost efficiency, but by the potential AI holds to disrupt competition and pave the way for entire new markets. In 2024, we’re going to see companies being built on top of generative AI, carving out segments that didn’t exist before. It’s important that CEOs and leaders understand the opportunity cost this presents to their business.
The early adopter advantage for AI is significant — companies that are investing in its capabilities to streamline operations and reduce overhead are also improving their end product or service at a fraction of the cost. Not only are these companies gaining valuable market share, but they are becoming drastically more scalable. In this sense, early adopters of AI are essentially becoming the asteroid that will hit competitors who sleep on the opportunity it presents.
As with any technology that presents great promise, it also comes with great responsibility. Many of the world’s greatest companies have been built by establishing strong cultures that center around their people. As we learn how generative AI can enhance ROI, redefine industries and create new frontiers of innovation, businesses need to navigate the landscape thoughtfully.
For companies like Accenture or Ernst and Young that rely on a vast workforce of human experts, for instance, the adoption of generative AI raises intriguing questions. What if the same level of work could be achieved with significantly fewer human resources? How would this reshape industries where human expertise is the core value proposition? These are complex questions that require careful consideration as we enter this new era of business.
Generative AI has opened Pandora’s box, and while the instinct to preserve jobs is noble, we must also pivot our thinking towards a more holistic approach. Rather than clinging to tasks that AI can accomplish more efficiently, leaders may be better off exploring reskilling opportunities and identifying areas where human talent is essential.
I believe the age of AI need not be a threat to our humanity, but an opportunity to redefine our values as leaders and the purpose of our businesses. By embracing this transformation thoughtfully, we can chart a course where technology and humanity coexist, enriching the other’s strengths.
As more companies navigate this complex path toward AI transformation, I believe those who embrace the journey will scale their organizations to new heights. On the other hand, those who stay stagnant may just find themselves in “asteroid territory.”
The logo of Japanese tech giant Rakuten logo seen at the Mobile World Congress 2019.
Paco Freire| SOPA Images | LightRocket via Getty Images
Japan’s Rakuten plans to launch its own artificial intelligence language model within the next two months, its CEO told CNBC in an interview that aired Monday.
It comes as the fintech-to-e-commerce giant looks to join other technology firms developing the rapidly growing technology.
Hiroshi “Mickey” Mikitani said the company is working on its own large language model, or LLM. These are huge algorithms trained on massive data sets that underpin artificial intelligence applications, such as OpenAI’s ChatGPT.
Rakuten has a number of businesses from banking to e-commerce and telecommunications, therefore has a large amount of “very unique” data to train its LLM on, according to Mikitani.
“Nobody has a dataset like we do,” he added.
The company plans to use the AI model internally to improve operational efficiency and marketing by 20%, Mikitani said.
He also wants to offer the model to third-party businesses to build on, much like Amazon or Microsoft do.
“So we can easily teach them [businesses], package it and provide the platform for them to completely they can use it for their business,” Mikitani said.
The CEO added that Rakuten is going to “have something within a couple of months.”
To date, major U.S. and Chinese technology giants have been launching their own large language models.
OpenAI, Amazon and Google are among the most notable in the U.S. In China, Baidu, Alibaba and Tencent have launched their own models too.
PARIS, ILE DE FRANCE, FRANCE – 2017/09/14: The Olympic Rings being placed in front of the Eiffel Tower in celebration of the French capital won the hosting right for the 2024 summer Olympic Games. (Photo by Nicolas Briquet/SOPA Images/LightRocket via Getty Images)
Sopa Images | Lightrocket | Getty Images
Training of elite athletes dates as far back as the Ancient Olympic Games, when so-called gymnastes advised runners, chariot racers, wrestlers and boxers on technique, nutrition and strength conditioning.
Fast forward to today’s Olympians prepping for next summer’s Paris Games. Their trainers and coaches adhere to the same Olympic motto — faster, higher, stronger — yet have the added benefit of millennia of ever-advancing technology, which now has been super-charged with artificial intelligence.
Trainers and coaches at U.S. Soccer, one of the 47 National Governing Bodies overseen by the United States Olympic and Paralympic Committee, are using AI technology to instantaneously identify and track player movements and ball positions. A suite of software tools allows them to study a variety of human performance metrics, such as body position, velocity, speed and timing in real time on the field of play.
“Utilizing advances in AI and computer vision, we’ve been able to track and study personalized analytics from a variety of sports to determine the strengths and deficiencies in an athlete’s movement and help them make data-informed training and competition plans that can help them improve their performance, as well as their own health,” said Mike Levine, director of performance innovation business operations at the USOPC, based in Colorado Springs, also the home of a high-tech Olympic training center.
While the USOPC and NGBs employ in-house experts in bleeding-edge technology development, data analytics and sports sciences and medicine, big tech companies lend their AI know-how as well. USA Surfing staff, for instance, has teamed up with Microsoft engineers to figure out how best to ride waves. They take digital videos of surfers in action and use AI to analyze data on body movement, surfboards and waves to determine what they did well and what could be improved.
“This work saves coaches and staff hundreds of hours of video tagging, facilitates the accumulation of more and higher-quality data and affords analysts and coaches significantly more time to analyze the data and implement learnings into real-life training and performance,” Levine said.
Creating 3-D models of athletes’ bodies with Intel technology
These are manifestations of computer vision systems, which use AI technology to replicate the capabilities of the human brain responsible for object recognition and classification. A commercial application, called 3D Athlete Tracking (3DAT), was developed by Intel‘s Olympic Technology Group a few years ago and is now being utilized by trainers in numerous sports. 3DAT incorporates sensor-less motion capture and digital video to create three-dimensional models of an athlete’s entire body, from head to toes, which trainers use to tweak and improve performance.
“We’re able to see ways athletes move and detect things not possible with just the human eye,” said Jonathan Lee, who as senior director of sports technology at Intel helped develop 3DAT and is now chief product officer at London-based sports tech company ai.io, which recently acquired the system from Intel.
3DAT has been adopted by Exos, a coaching company in Scottsdale, Arizona, that trains college football players for the National Football League’s annual scouting combine, an evaluation ahead of the league’s yearly draft. “Exos uses 3DAT to analyze the 40-yard dash and help players get faster,” Lee said. Digital video cameras, mounted on timing gates incrementally positioned along the course, capture data on how a runner comes off the line, his acceleration and velocity, and his body’s angle of attack.
The data instantaneously constructs a personalized skeletal model of each player for immediate review. Before a player’s next sprint, a trainer might say, “You need to be more upright or lean forward, and give him tips on how to achieve that,” Lee said.
The NFL-Amazon digital player and concussion-risk tracking
The NFL itself is harnessing AI and computer vision to enhance its Digital Athlete program, developed in partnership with Amazon Web Services beginning in 2019. The Digital Athlete provides a complete view of each NFL players’ experience by analyzing data from his training and game activity, which is captured by sensors and tags in equipment and hours of video from cameras in stadiums. Computer vision and machine learning systems track speed, collisions, blocks and tackles. This data is shared with clubs and allows teams to precisely understand what players need to stay healthy, recover quickly and perform at their best.
“AI and machine learning are the backbone of the program,” said Jennifer Langton, NFL senior vice president of health and safety innovation. “We’re able to analyze a substantial amount of data and automatically generate insights into which players might benefit from altering either training or recovery routines, a process that used to be so manual and cumbersome.”
The AI was taught to identify trauma by repeated exposure to and digestion of digital video images of helmets from all angles, Langton said, and then to cross-reference visual information from statistical data to determine what player was wearing what helmet. “With enough practice, the AI becomes exponentially faster and more reliable than humans at accurately identifying and classifying head collisions throughout a game and the season,” she said, allowing trainers and coaches to see which players are due to reduce their workloads and which have room for a more intensive workout.
The Digital Athlete program was rolled out as a pilot with four NFL teams last year and this season is available to all 32 franchises via a dedicated online portal. “The portal provides teams with a daily training load and risk-mitigation information, as well as league-wide injury trends and benchmarks they hadn’t had before,” Langton said, adding that the NFL will assess the data at the end of the season to evaluate tangible results of the program.
‘The next big thing’: Twin hearts of elite athletes
Another AI-enabled technology that’s making its way into elite athlete training is the digital twin, a virtual replica of a physical object, process or system that can be used to simulate, predict and improve real-world scenarios. Tata Consultancy Services, headquartered in Mumbai, recently announced a partnership with French tech developer Dassault Systèmes to produce a digital twin heart, mimicking the flesh-and-blood one of Des Linden, a two-time Olympic marathoner and winner of the 2018 Boston Marathon (sponsored by TCS, along with the races in New York, Chicago and London).
Des Linden makes her way to the finish line during the 127th Boston Marathon in Boston, Massachusetts on April 17, 2023.
Joseph Prezioso | Afp | Getty Images
Linden’s avatar organ — created using AI-analyzed data from CT scans and MRIs — can simulate her heart rate, blood flow and oxygen levels, providing instant feedback that can be interpreted to adjust her training and competition. “We want to understand what is a safe zone for Des’ trainer to put her through,” said Dr. Srinivasan Jayaraman, a principal scientist at TCS. Instead of having her run on a treadmill or outdoors, “We can run simulations using her digital twin heart to vary different cardiovascular parameters and fine-tune her training.”
Linden is no stranger to sports tech, from online message boards back in her high school days for remotely comparing times with other runners to today’s state-of-the-art running shoes that world-class marathoners have broken records wearing. “The digital twin heart is going to be the next big thing,” she said. “Being able to map out [my training] and see the gains and drawbacks ahead of time will allow me to work smarter, not harder.”
That’s what Linden, aided by her digital twin heart, will be doing to train for the 2024 Olympic marathon trials in February. Qualifying for her third Team USA slot “will be a tough task,” said the 40-year-old runner, “but I’ll take a crack at it.”
AI and sports training diets
Although there’s no news yet of a digital twin of the human digestive system, AI is involved in planning Olympic athletes’ diet and nutrition. Alicia Glass, a senior sports dietician for the USOPC, designs meal plans for about 300 athletes with USA Track and Field and USA Swimming, a labor-intensive, hand-written task that’s been simplified with an AI-powered app called Notemeal. “They collected data from 37 dieticians from professional sports teams and organizations and used those data sets to generate individualized meal plans,” she said. “The value-add is that it’s a network of sports dieticians working with the best of the best athletes in the world.”
Glass still relies on her professional skills to understand the events each athlete competes in, their training regimens and goals, as well as their genetics, lean body mass and metabolic rate. Even athletes who train and compete in the same events require totally individualized meal plans, she said. “Notemeal makes that process a lot easier,” she said.
The athletes access Notemeal with a smartphone app. “I hit a toggle on my phone, and they get a text saying a meal has been created for you,” Glass said, adding that the app also applies AI to design personalized shopping lists and recipes.
Glass won’t claim that high-tech dietary planning will win medals next summer in Paris, but “many athletes would admit it helps improve their lifestyle because they’re more aware” of their personal fueling needs.
Linden says there is no turning back from the increasing role of technology in the lives of elite athletes. “Let’s just personalize the heck out of training and make sure we’re getting the maximum gains without setbacks from overworking,” she said.
In just one year, artificial intelligence has gone from being the stuff of science fiction movies to being used as a tool to help us polish our resumes and plan European getaways.
But many tech experts don’t appear to be too worried about that happening any time soon.
“AI can certainly recognize your house cat, but it’s not going to solve world hunger,” Theo Omtzigt, chief technology officer at Lemurian Labs, tells CNBC Make It.
One reason AI likely won’t replace people completely is both pretty simple and complex: math.
Large language models, a subset of generative AI, rely on powerful mathematical formulas to process and identify patterns in vast amounts of data to convert users’ prompts into new text, image, video or audio outputs.
But human intelligence goes far beyond pattern recognition. That’s why the mathematical models powering current generative AI systems are “relatively super simple,” Omtzigt says.
“Right now, the machine learns how to recognize a cat and what it will look like in different lighting,” he says. “We would have to progress a lot deeper in our understanding of creative thoughts, ethics and consciousness before we would even have the building blocks to think of how to create an AI that would be able to wipe out humanity.”
Another reason tech experts don’t believe AI will replace people is because it gains knowledge differently than humans.
“Generative AI and machine learning techniques are very heavily based on correlation, as opposed to causation,” Justin Lewis, BP’s vice president of incubation and engineering, said Thursday during a panel discussion at the AI Summit New York2023.
After processing many images of rain, an AI model may learn to correlate rain with clouds because in every picture of rain, there are clouds. However, a human learns that clouds produce rain, says James Brusseau, a philosophy professor at Pace University who also teaches AI ethics at the University of Trento in Italy.
“AI and humans are both knowledge producers, just like the sculptor and painter are both artists,” he tells CNBC Make It. “But they will be forever, in my mind, be distinct and separated. One will never be better than the other so much as they will just be different.”
Fears about AI replacing humans aren’t completely unwarranted, but it won’t be the systems on their own that take over.
“There’s definitely going to be a difference between those that use AI and those that don’t,” Trevor Back, chief product officer at Speechmatics, said during Thursday’s panel discussion at the AI Summit New York 2023.
“If you don’t use AI, you are going to struggle since most roles will use some form of AI in the way that they act,” he said.
For example, many tech experts currently see AI being used as a tool that helps people boost their productivity. A software engineer may use AI to speed up the code review process and identify potential errors they or another human may have missed.
Since AI doesn’t seem to be disappearing any time soon, one of the best ways to fend off worries about being replaced by it is to explore how these systems work and how they can help you, Brusseau says.
“Curiosity is good,” he says. “You have to say ‘I’m not afraid of what the machine might do to me. I’m interested in what it can do for me.’”
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