Bloomberg LP has developed an AI model using the same underlying technology as OpenAI’s GPT, and plans to integrate it into features delivered through its terminal software, a company official said in an interview with CNBC.
Bloomberg says that Bloomberg GPT, an internal AI model, can more accurately answer questions like “CEO of Citigroup Inc?”, assess whether headlines are bearish or bullish for investors, and even write headlines based on short blurbs.
Large language models trained on terabytes of text data are the hottest corner of the tech industry. Giants such as Microsoft and Google are racing to integrate the technology into their products, and artificial intelligence startups are regularly raising funds at valuations over $1 billion.
Bloomberg’s move shows how software developers in many industries beyond Silicon Valley see state-of-the-art AI like GPT as a technical advancement allowing them to automate tasks that used to require a human.
“Both the capabilities of GPT-3 and the way that it achieved its performance through language modeling wasn’t something that I expected,” said Gideon Mann, head of ML Product and Research at Bloomberg. “So when that came out, we were like, ‘OK, this is going to change the way that we do NLP here.'”
NLP stands for natural language processing, the part of machine learning that focuses on deriving meaning from words.
The move also shows how the AI market may not be dominated by giants with massive amounts of generalized data.
Building large language models is expensive, requiring access to supercomputers and millions of dollars to pay for them, and some have wondered if OpenAI and Big Tech companies would develop an insurmountable lead. In this scenario, they would be the winners, and simply sell access to their AIs to everybody else.
But Bloomberg’s GPT doesn’t use OpenAI. The company was able to use freely available, off-the-shelf AI methods and apply them to its massive store of proprietary — if niche — data.
So far, Bloomberg says its GPT shows promising results doing tasks like figuring out whether a headline is good or bad for a company’s financial outlook, changing company names to stock tickers, figuring out the important names in a document, and even answering basic business questions like who the CEO of a company is.
It also can do some “generative AI” applications, like suggesting a new headline based on a short paragraph.
One example in the paper:
Input: “The US housing market shrank in value by $2.3 trillion, or 4.9%, in the second half of 2022, according to Redfin. That’s the largest drop in percentage terms since the 2008 housing crisis, when values slumped 5.8% during the same period”
Output: “Home Prices See Biggest Drop in 15 Years.”
How it could be used
OpenAI’s GPT is often called a “foundational” model because it wasn’t intended for a specific task.
Bloomberg’s approach is different. It was specifically trained on a large number of financial documents collected by the firm over the years to create a model that’s especially fluent in money and business.
In contrast, OpenAI’s GPT was trained on terabytes of text, the vast majority of which had nothing to do with finance.
About half of the data used to create Bloomberg’s model comes from nonfinancial sources scraped from the web, including GitHub, YouTube subtitles, and Wikipedia.
But Bloomberg also added over 100 billion words from a proprietary dataset called FinPile, which includes financial data the firm has accumulated over the last 20 years, including securities filings, press releases, Bloomberg News stories, stories from other publications and a web crawl focused on financial webpages.
It turns out that adding specific training materials increased accuracy and performance enough on financial tasks that Bloomberg is planning to integrate its GPT into features and services accessed through the company’s Terminal product, although Bloomberg is not planning a ChatGPT-style chatbot.
One early application would be to transform human language into the specific database language that Bloomberg’s software uses.
For example, it would transform “Tesla price” into “(get(px_last) for([‘TSLA US Equity’])”.
Another possibility would be for the model to do behind-the-scenes work cleaning data and doing other errands on the application’s back end.
But Bloomberg is also looking at using artificial intelligence to power features that could help financial professionals save time and stay on top of the news.
“There’s a lot of work we’re doing to help clients address that data deluge of news stories, whether that’s through summarization, or monitoring, or being able to ask questions on those news stories or transcripts. There are a lot of applications there,” Mann said.
Altimeter Capital CEO Brad Gerstner said Thursday that he’s moving out of the “bomb shelter” with Nvidia and into a position of safety, expecting that the chipmaker is positioned to withstand President Donald Trump’s widespread tariffs.
“The growth and the demand for GPUs is off the charts,” he told CNBC’s “Fast Money Halftime Report,” referring to Nvidia’s graphics processing units that are powering the artificial intelligence boom. He said investors just need to listen to commentary from OpenAI, Google and Elon Musk.
President Trump announced an expansive and aggressive “reciprocal tariff” policy in a ceremony at the White House on Wednesday. The plan established a 10% baseline tariff, though many countries like China, Vietnam and Taiwan are subject to steeper rates. The announcement sent stocks tumbling on Thursday, with the tech-heavy Nasdaq down more than 5%, headed for its worst day since 2022.
The big reason Nvidia may be better positioned to withstand Trump’s tariff hikes is because semiconductors are on the list of exceptions, which Gerstner called a “wise exception” due to the importance of AI.
Nvidia’s business has exploded since the release of OpenAI’s ChatGPT in 2022, and annual revenue has more than doubled in each of the past two fiscal years. After a massive rally, Nvidia’s stock price has dropped by more than 20% this year and was down almost 7% on Thursday.
Gerstner is concerned about the potential of a recession due to the tariffs, but is relatively bullish on Nvidia, and said the “negative impact from tariffs will be much less than in other areas.”
He said it’s key for the U.S. to stay competitive in AI. And while the company’s chips are designed domestically, they’re manufactured in Taiwan “because they can’t be fabricated in the U.S.” Higher tariffs would punish companies like Meta and Microsoft, he said.
“We’re in a global race in AI,” Gerstner said. “We can’t hamper our ability to win that race.”
YouTube on Thursday announced new video creation tools for Shorts, its short-form video feed that competes against TikTok.
The features come at a time when TikTok, which is owned by Chinese company ByteDance, is at risk of an effective ban in the U.S. if it’s not sold to an American owner by April 5.
Among the new tools is an updated video editor that allows creators to make precise adjustments and edits, a feature that automatically syncs video cuts to the beat of a song and AI stickers.
The creator tools will become available later this spring, said YouTube, which is owned by Google.
Along with the new features, YouTube last week said it was changing the way view counts are tabulated on Shorts. Under the new guidelines, Shorts views will count the number of times the video is played or replayed with no minimum watch time requirement.
Previously, views were only counted if a video was played for a certain number of seconds. This new tabulation method is similar to how views are counted on TikTok and Meta’s Reels, and will likely inflate view counts.
“We got this feedback from creators that this is what they wanted. It’s a way for them to better understand when their Shorts have been seen,” YouTube Chief Product Officer Johanna Voolich said in a YouTube video. “It’s useful for creators who post across multiple platforms.”
CEO of Meta and Facebook Mark Zuckerberg, Lauren Sanchez, Amazon founder Jeff Bezos, Google CEO Sundar Pichai, and Tesla and SpaceX CEO Elon Musk attend the inauguration ceremony before Donald Trump is sworn in as the 47th U.S. president in the U.S. Capitol Rotunda in Washington, Jan. 20, 2025.
Saul Loeb | Via Reuters
Technology stocks plummeted Thursday after President Donald Trump’s new tariff policies sparked widespread market panic.
Apple led the declines among the so-called “Magnificent Seven” group, dropping nearly 9%. The iPhone maker makes its devices in China and other Asian countries. The stock is on pace for its steepest drop since 2020.
Other megacaps also felt the pressure. Meta Platforms and Amazon fell more than 7% each, while Nvidia and Tesla slumped more than 5%. Nvidia builds its new chips in Taiwan and relies on Mexico for assembling its artificial intelligence systems. Microsoft and Alphabet both fell about 2%.
The drop in technology stocks came amid a broader market selloff spurred by fears of a global trade war after Trump unveiled a blanket 10% tariff on all imported goods and a range of higher duties targeting specific countries after the bell Wednesday. He said the new tariffs would be a “declaration of economic independence” for the U.S.
Companies and countries worldwide have already begun responding to the wide-sweeping policy, which included a 34% tariff on China stacked on a previous 20% tax, a 46% duty on Vietnam and a 20% levy on imports from the European Union.
China’s Ministry of Commerce urged the U.S. to “immediately cancel” the unilateral tariff measures and said it would take “resolute counter-measures.”
The tariffs come on the heels of a rough quarter for the tech-heavy Nasdaq and the worst period for the index since 2022. Stocks across the board have come under pressure over concerns of a weakening U.S. economy. The Nasdaq Composite dropped nearly 5% on Thursday, bringing its year-to-date loss to 13%.
Trump applauded some megacap technology companies for investing money into the U.S. during his speech, calling attention to Apple’s plan to spend $500 billion over the next four years.