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Sundar Pichai, chief executive officer of Alphabet Inc., during the Google I/O Developers Conference in Mountain View, California, on Wednesday, May 10, 2023.

David Paul Morris | Bloomberg | Getty Images

Google’s new large language model, which the company announced last week, uses almost five times as much training data as its predecessor from 2022, allowing its to perform more advanced coding, math and creative writing tasks, CNBC has learned.

PaLM 2, the company’s new general-use large language model (LLM) that was unveiled at Google I/O, is trained on 3.6 trillion tokens, according to internal documentation viewed by CNBC. Tokens, which are strings of words, are an important building block for training LLMs, because they teach the model to predict the next word that will appear in a sequence.

Google’s previous version of PaLM, which stands for Pathways Language Model, was released in 2022 and trained on 780 billion tokens.

While Google has been eager to showcase the power of its artificial intelligence technology and how it can be embedded into search, emails, word processing and spreadsheets, the company has been unwilling to publish the size or other details of its training data. OpenAI, the Microsoft-backed creator of ChatGPT, has also kept secret the specifics of its latest LLM called GPT-4.

The reason for the lack of disclosure, the companies say, is the competitive nature of the business. Google and OpenAI are rushing to attract users who may want to search for information using conversational chatbots rather than traditional search engines.

But as the AI arms race heats up, the research community is demanding greater transparency.

Since unveiling PaLM 2, Google has said the new model is smaller than prior LLMs, which is significant because it means the company’s technology is becoming more efficient while accomplishing more sophisticated tasks. PaLM 2, according to internal documents, is trained on 340 billion parameters, an indication of the complexity of the model. The initial PaLM was trained on 540 billion parameters.

Google didn’t immediately provide a comment for this story.

A.I. takes center stage at Alphabet's annual Google I/O conference

Google said in a blog post about PaLM 2 that the model uses a “new technique” called “compute-optimal scaling.” That makes the the LLM “more efficient with overall better performance, including faster inference, fewer parameters to serve, and a lower serving cost.”

In announcing PaLM 2, Google confirmed CNBC’s previous reporting that the model is trained on 100 languages and performs a broad range of tasks. It’s already being used to power 25 features and products, including the company’s experimental chatbot Bard. It’s available in four sizes, from smallest to largest: Gecko, Otter, Bison and Unicorn. 

PaLM 2 is more powerful than any existing model, based on public disclosures. Facebook’s LLM called LLaMA, which it announced in February, is trained on 1.4 trillion tokens. The last time OpenAI shared ChatGPT’s training size was with GPT-3, when the company said it was trained on 300 billion tokens at the time. OpenAI released GPT-4 in March, and said it exhibits “human-level performance” on many professional tests.

LaMDA, a conversation LLM that Google introduced two years ago and touted in February alongside Bard, was trained on 1.5 trillion tokens, according to the latest documents viewed by CNBC.

As new AI applications quickly hit the mainstream, controversies surrounding the underlying technology are getting more spirited.

El Mahdi El Mhamdi, a senior Google Research scientist, resigned in February over the company’s lack of transparency. On Tuesday, OpenAI CEO Sam Altman testified at a hearing of the Senate Judiciary subcommittee on privacy and technology, and agreed with lawmakers that a new system to deal with AI is needed.

“For a very new technology we need a new framework,” Altman said. “Certainly companies like ours bear a lot of responsibility for the tools that we put out in the world.”

— CNBC’s Jordan Novet contributed to this report.

WATCH: OpenAI CEO Sam Altman calls for A.I. oversight

OpenAI CEO Sam Altman call fors A.I. oversight in testimony to congress

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How Huawei ascended from telecoms to become China’s ‘jack of all trades’ AI leader

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How Huawei ascended from telecoms to become China's 'jack of all trades' AI leader

The Huawei booth at the Mobile World Congress in Barcelona, 2025.

Arjun Kharpal | CNBC

Despite being beaten down by years of U.S. trade restrictions, China’s telecom giant Huawei has quietly emerged as one of the country’s fiercest competitors across the entire AI landscape.  

Not only does the Shenzhen-based firm appear to represent Beijing’s answer to American AI chip darling Nvidia, but it has also been an early adopter of monetizing artificial intelligence models in industrial applications. 

“Huawei has been forced to shift and expand its core business focus over the past decade… due to a variety of external pressures on the company,” said Paul Triolo, partner and senior vice president for China at advisory firm DGA-Albright Stonebridge Group.

This expansion has seen the company get involved in everything from smart cars and operating systems to the technologies needed for the AI boom, such as advanced semiconductors, data centers, chips and large language models. 

“No other technology company has been able to be competent in so many different sectors with high levels of complexity and barriers to entry,” Triolo said. 

This year, Nvidia CEO Jensen Huang has become increasingly vocal in calling Huawei “one of the most formidable technology companies in the world.” He has also warned that Huawei will replace Nvidia in China if Washington continues to restrict U.S. chip firms’ exports to the Asian country.

Nvidia surpassed $4 trillion in market capitalization last week to become the world’s most valuable company. Its cutting-edge processors and a related “CUDA” computing system remain the industry standard for training generative AI models and applications. 

But that moat may be narrowing, as Huawei proves that it not only does it all, it does it well. While challenging American AI stalwarts like Nvidia is a tall order, the company’s history shows why it can’t be counted out.

Nvidia CEO Jensen Huang calls Huawei a formidable competitor

Telephone switches to national champion

Huawei, which now employs more than 208,000 people across over 170 markets, came from humble beginnings. Founded by ambitious entrepreneur Ren Zhengfei in 1987 out of an apartment in Shenzhen, the firm started as a small telephone switch distributor.

As it grew into a telecoms player, it gained traction by targeting less developed markets such as Africa, the Middle East, Russia and South America, before eventually expanding to places like Europe.

By 2019, Huawei would be well-positioned to capitalize on the global 5G rollout, becoming a leader in the market. Around this time, it had also blossomed into one of the world’s largest smartphone manufacturers and was even designing smartphone chips through its chip design subsidiary, HiSilicon. 

But Huawei’s success also attracted increasing scrutiny from governments outside China, particularly the U.S., which has frequently accused Huawei’s technology of posing a national security threat. The Chinese company has refuted such risks

The export controls have ironically pushed Huawei into the arms of the Chinese government in a way that CEO Ren Zhengfei always resisted.

Paul Triolo

partner and senior vice president for China at DGA-Albright Stonebridge Group

Huawei’s business suffered a major setback in 2019 when it was placed on a U.S. trade blacklist, preventing American companies from doing business with it. 

As the impact of the sanctions kicked in, Huawei’s consumer business – once the company’s largest by revenue – halved to about $34 billion in 2021 from the year before.

The company still managed a breakthrough on AI chips, and pressed ahead despite additional U.S. restrictions in 2020 that cut the company off from chipmaker Taiwan Semiconductor Manufacturing Co. A year earlier, Huawei officially launched its Ascend 910 AI processing chip as part of a strategy to build a “full-stack, all-scenario AI portfolio” and to become a provider of AI computing power.

But the U.S. targeting of Huawei also had the effect of turning the company into a martyr-like figure in China, building upon attention it received in 2018 when Meng Wanzhou, Huawei’s CFO and daughter of Ren, was arrested in Canada for alleged violations of Iran sanctions.

As the U.S.-China tech war continued to expand and broad advanced chip restrictions were placed on China, Huawei was an obvious choice to become a national champion in the race, with more impetus and state backing for its AI plans. 

“The export controls have ironically pushed Huawei into the arms of the Chinese government in a way that CEO Ren Zhengfei always resisted,” Triolo said. In this way, the restrictions also became “the steroids” for Huawei’s AI hardware and software stack.

The comeback 

After another year of declining sales in the consumer segment, the unit started to turn around in 2023 with the release of a smartphone that analysts said contained an advanced chip made in China. 

The 5G chip came as a shock to many in the U.S., who didn’t expect Huawei to reach that level of advancement so quickly without TSMC. Instead, Huawei was reportedly working with Chinese chipmaker SMIC, a company that has also been blacklisted by the U.S.

While semiconductor analysts said the scale that Huawei and SMIC could produce these chips was severely limited, Huawei nonetheless had proved it was back in the advanced chip game. 

It was also around this time that reports began surfacing about Huawei’s new AI processor chip, the Ascend 910B, with the company looking to seize upon gaps left by export controls on Nvidia’s most advanced chips. Mass production of the next-generation 910C is reportedly already on the way. 

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To fill the void left by Nvidia, Huawei “has been making big strides in replicating the performance of high-end GPUs using combinations of lower chips,” said Jeffrey Towson, managing partner at TechMoat Consulting.

In April, Huawei unveiled its “AI CloudMatrix 384”, a system that links 384 Ascend 910C chips in a cluster within data centers. Analysts have said CloudMatrix is able to outperform Nvidia’s system, the GB200 NVL72, on some metrics.

Huawei isn’t just catching up, “it’s redefining how AI infrastructure works,” Forrester analysts said in a report last month about CloudMatrix.

Meanwhile, Huawei has also developed its own “CANN” software system that acts as an alternative to Nvidia’s CUDA

“Winning the AI race isn’t just about faster chips. It also includes delivering the tools developers need to build and deploy large-scale models,” Forrester’s report said, though authors noted that Huawei’s products are still not integrated enough with other commonly used tools for developers to switch over quickly from Nvidia.

The ‘Ascend Ecosystem Strategy’

Jensen Huang: China is not behind the U.S. in AI development

These data centers, in turn, have provided the training capabilities and computing power used by Huawei’s suite of AI models under its Pangu series. 

Unlike other general-purpose AI models like OpenAI’s GPT-4 or Google’s Gemini Ultra 1.0, Huawei’s Pangu model is designed to support more industry-specific applications across the medical, finance, government, industrial and automotive sectors. Pangu has already been applied in more than 20 industries over the last year, the company said last month

Rolling out such AI applications often involves having Huawei tech staff working for months at the project site, even if it’s in a remote coal mine, Jack Chen, vice president of the marketing department for Huawei’s oil, gas and mining business unit, which provides digital and intelligent solutions to transform these industries, told CNBC.

That research enabled the company in May to deploy more 100 electric-powered trucks that can autonomously transport dirt or coal using the telecom company’s 5G network, AI and cloud computing services.

And it’s not limited to China. The technology can “be replicated on a large scale in Central Asia, Latin America, Africa, and the Asia-Pacific,” Chen said.

Huawei has also open-sourced the Pangu models, in a move it said would help it expand overseas and further its “Ascend ecosystem strategy,” which refers to its AI products built around its Ascend chips.

Speaking to CNBC’s “Squawk Box Asia” on Thursday, Patrick Moorhead of Moor Insights & Strategy said he expected Huawei to push Ascend in countries part of China’s Belt and Road Initiative — an investment and development project aimed at emerging markets. 

Over a period of five to 10 years, the company could begin to build serious market share in these countries, in the same way it once did with its telecommunications business, he added.

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Astronomer CEO Andy Byron resigns after viral Coldplay kiss-cam controversy

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Astronomer CEO Andy Byron resigns after viral Coldplay kiss-cam controversy

Chris Martin of Coldplay performs at the O2 Shepherd’s Bush Empire on October 12, 2021 in London, England.

Simone Joyner | Getty Images Entertainment | Getty Images

Astronomer, the technology company that faced backlash after its CEO was allegedly caught in an affair at a Coldplay concert, said the CEO has resigned, the company announced Saturday.

“Andy Byron has tendered his resignation, and the Board of Directors has accepted,” the company said in a statement. “The Board will begin a search for our next Chief Executive as Cofounder and Chief Product Officer Pete DeJoy continues to serve as interim CEO.”

Byron was shown on a big screen at a Coldplay concert on Wednesday with his arms around the company’s chief people officer, Kristin Cabot. Byron, who is married with children, immediately hid when the couple was shown on screen. Lead singer Chris Martin said, “Either they’re having an affair or they’re just very shy.” A concert attendee’s video of the affair went viral.

In May, Astronomer announced a $93 million investment round led by Bain Ventures and other investors, including Salesforce Ventures.

Byron’s resignation comes after Astronomer said Friday that it had launched a “formal investigation” into the matter, and the CEO was placed on administrative leave.

“Before this week, we were known as a pioneer in the DataOps space, helping data teams power everything from modern analytics to production AI,” the company said in its Saturday statement. “Our leaders are expected to set the standard in both conduct and accountability, and recently, that standard was not met.”

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Nvidia CEO Jensen Huang sells an additional $12.94 million worth of shares

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Nvidia CEO Jensen Huang sells an additional .94 million worth of shares

Jensen Huang, co-founder and CEO of Nvidia Corp., speaks during a news conference in Taipei on May 21, 2025.

I-hwa Cheng | Afp | Getty Images

Nvidia CEO Jensen Huang sold 75,000 shares on Friday, valued at about $12.94 million, according to a filing with the U.S. Securities and Exchange Commission. 

Friday’s sale is part of a plan adopted in March for Huang to sell up to 6 million shares of the leading artificial intelligence company. Earlier this week, Huang sold 225,000 shares of the chipmaker, totaling about $37 million, according to a separate SEC filing. The CEO began trading stock per the plan last month.

Surging demand for AI and the graphics processing units that power large language models has significantly boosted Huang’s net worth and pushed Nvidia’s market capitalization beyond $4 trillion, making it the world’s most valuable company.

Nvidia announced this week that it expects to resume sales of its H20 chips to China soon, following signals from the Trump administration that it would approve export licenses. Earlier this year, U.S. officials had stated that Nvidia would require special permission to ship the chips, which are specifically designed for the Chinese market.

“The U.S. government has assured NVIDIA that licenses will be granted, and NVIDIA hopes to start deliveries soon,” the company said in a statement on Tuesday. Huang said during a news conference on Wednesday in Beijing that he wants to sell chips more advanced than the H20 to China at some point.

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