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CEO of writer.com May Habib attends the Harper’s Bazaar At Work Summit, in partnership with Porsche and One&Only One Za’abeel, at Raffles London at The OWO on November 21, 2023 in London, England.

Dave Benett | Getty Images

San Francisco-based AI startup Writer debuted a large artificial intelligence model on Wednesday to compete with enterprise offerings from OpenAI, Anthropic and others. But, unlike some of those competitors, it doesn’t need to spend as much to train its AI.

The company told CNBC it spent about $700,000 to train its latest model, including the data and GPUs, compared to the millions of dollars competing startups spend to build their own models. Its strategy has caught the attention of investors.

Writer is raising up to $200 million at a $1.9 billion valuation, according to a source familiar with the situation who spoke with CNBC. That’s nearly quadruple the company’s valuation last September, when it raised $100 million at a valuation of more than $500 million.

The company cuts costs using synthetic data, or data created by AI. It’s designed to mimic the real-world information that’s usually fed into models without compromising privacy and is becoming a more popular method for training.

A study by AI researchers revised in June found that if current AI development trends continue, tech companies will “fully exhaust” the publicly available training data between 2026 and 2032, writing that “human-generated public text data cannot sustain scaling beyond this decade.”

Amazon has used synthetic data in training Alexa, Meta has used it to fine-tune its Llama models and Microsoft-backed OpenAI is incorporating it into its models, according to job descriptions posted by the company. Some experts, however, have warned that synthetic data should be used cautiously, as it has the potential to degrade model performance and exacerbate existing biases.

Waseem Alshikh, Writer’s co-founder and CTO, told CNBC that Writer has been working on its synthetic data pipeline for years.

“There’s some confusion in the industry about the definition of ‘synthetic’ data,” Alshikh said. “To be clear, we don’t train our models on fake or hallucination data, and we don’t use a model to generate random data… We take real, factual data and convert it to synthetic data that is specifically structured in a clearer and cleaner way for model training.”

The company’s generative AI allows corporate clients to use its large language models (LLMs) to generate human-sounding text for anything from LinkedIn posts to job descriptions to mission statements, as well as data analysis and summarization. The company has more than 250 enterprise customers, including Accenture, Uber, Salesforce, L’Oreal and Vanguard, who use the tech across sectors like support, IT, operations, sales, and marketing.

The generative AI market is poised to top $1 trillion in revenue within a decade. To date in 2024, investors have pumped $26.8 billion into 498 generative AI deals, according to PitchBook, and companies in the sector raised $25.9 billion in 2023, up more than 200% from 2022.

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Google announces new health-care AI updates for Search

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Google announces new health-care AI updates for Search

A Google corporate logo hangs above the entrance to their office at St. John’s Terminal on March 11, 2025, in New York City.

Gary Hershorn | Corbis News | Getty Images

Google on Tuesday announced health-care updates to Search, including a way for people with specific health conditions to compare their experiences with others.

The company unveiled a new feature called “What People Suggest,” which uses AI to pull together online commentary from patients with similar diagnoses. A patient with arthritis would be able to look up how other people with the condition approach exercise, for instance. The feature is available on mobile devices in the U.S., Google said.

Google said it has also expanded its knowledge panels, or the information boxes that appear to the right of search results, to cover “thousands” more health topics. The panels are coming to new countries and languages, including Spanish, Japanese and Portuguese, starting on mobile devices.

The tech giant has launched several health-care projects and features over the years, but it has struggled to outline a consistent business strategy within the sector. The company built out a formal Google Health unit starting around 2018, which swelled to more than 500 employees, but it was dissolved in 2021.

Karen DeSalvo, Google’s chief health officer, told CNBC months later that the company was “still all-in on health.”

In recent years, many of Google’s health-care initiatives have centered around AI.

Google introduced artificial intelligence summaries called AI Overviews last year, and the feature shows a quick summary of answers to search questions at the very top of Search. The rollout was rocky, as users were quick to share examples AI tool giving incorrect and controversial responses, like encouraging users to add glue to pizza.

AI Overviews appear for some health-related queries, like “How do I know if I have the flu?” But some experts have encouraged users to use caution with these answers, according to a December report from The Senior List. Out of more than 200 health searches, a panel of medical experts said 70% Google’s AI Overviews were considered risky.

Google said Tuesday that recent health-focused advancements with its Gemini models have allowed the company to improve AI Overviews for health topics.

In late 2023, Google announced MedLM, a suite of AI models designed specifically for health-care, to help clinicians and researchers carry out complex studies, summarize doctor-patient interactions and complete other tasks.

The company also unveiled Vertex AI Search for Healthcare that year, which is a generative AI tool that clinicians can use to search for information across disparate medical records.

Watch: Google to acquire cloud security startup Wiz for $32 billion.

Google to acquire cloud security startup Wiz for $32 billion

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Google to acquire cloud security startup Wiz for $32 billion

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Google to acquire cloud security startup Wiz for  billion

The Wiz website on a smartphone arranged in New York, US, on Tuesday, July 16, 2024. 

Gabby Jones | Bloomberg | Getty Images

Google on Tuesday signed a “definitive agreement” to acquire Wiz, a New York-based cloud security startup, for $32 billion in an all-cash deal.

The deal, which will be Google’s largest-ever acquisition, will improve its cloud security offering in a world of advancing artificial intelligence and cybersecurity threats. Wiz will become a part of the company’s cloud business. Google said it expects to close the deal in 2026.

“Google Cloud is a leader in cloud infrastructure, with deep AI expertise and a track record of industry-leading security innovation,” Google said in a release. “Bringing all this to Wiz will help make their solutions even better and more scalable, benefiting customers and partners across all major clouds.”

The acquisition comes after CNBC reported in July that Wiz had walked away from a potential $23 billion acquisition by Google and announced to employees that it would pursue an initial public offering instead.

“Saying no to such humbling offers is tough,” Wiz co-founder Assaf Rappaport wrote to employees in a July memo obtained by CNBC. At the time, a source familiar with the matter told CNBC that Wiz walked away from the deal in part due to antitrust and investor concerns.

Before talks with Google were reported, Wiz had set its sights on two goals: an IPO and $1 billion in annual recurring revenue. In the memo at the time, Rappaport wrote that the company would pursue those milestones.

Wiz was founded in 2020 and has grown rapidly under Rappaport, with the company hitting $100 million in annual recurring revenue after just 18 months. The company’s cloud security products include prevention, active detection and response, a portfolio that’s appealed to large firms and would have helped Google compete with Microsoft, which also sells security software.

“Becoming part of Google Cloud is effectively strapping a rocket to our backs: it will accelerate our rate of innovation faster than what we could achieve as a standalone company,” Rappaport said in a blog post Tuesday.

Google has a long history in dealmaking and snatching up smaller companies to broaden its offerings to customers. Its largest deal before Wiz was the $12.5 billion acquisition of hardware marker Motorola in 2012. Two years later, the company sold some assets to Lenovo for $2.9 billion. Google has also made cybersecurity acquisitions in the past, paying $5.4 billion for Mandiant in 2022.

Wiz’s products will still work on competitor platforms including Amazon Web Services, Microsoft Azure and Oracle Cloud, the companies said. The Wall Street Journal first reported Monday that the companies were in advanced discussions.

While the agreement may still draw government scrutiny, many on Wall Street have been hopeful that President Donald Trump’s new White House administration will be more amenable to tech industry deals. Alphabet is currently battling an antitrust suit over its online search dominance.

— CNBC’s Jennifer Elias, Jordan Novet and Rohan Goswami contributed to this report.

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Baidu, once China’s generative AI leader, is battling to regain its position

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Baidu, once China’s generative AI leader, is battling to regain its position

Pictured here is the Ernie bot mobile interface, with the Baidu search engine home page in the background.

Future Publishing | Future Publishing | Getty Images

Chinese tech giant Baidu has released two new free-to-use artificial intelligence models as it vies to regain its leading position in the country’s fiercely competitive AI space. 

The Baidu models launched Sunday included the company’s first reasoning-focused model, and come ahead of plans to move toward an open-source strategy. 

However, experts told CNBC that while the release of the models is a positive development for Baidu, they also highlight how it is playing catch up as its Ernie bot — one of China’s earliest versions of a ChatGPT-like chatbot — struggles to gain widespread adoption. 

“The new models make Baidu more competitive since the company has been lagging behind in a reasoning model release,” Lian Jye Su, chief analyst at Omdia, told CNBC.

A reasoning model is a large language model that breaks down tasks into smaller pieces and considers multiple approaches before generating a response. It is designed to process complex problems in a similar way to humans.

Chinese startup DeepSeek upended the global AI race and transformed China’s ecosystem in January when it released its R1 reasoning model, which rivaled American competitors despite costing a fraction of the price.

Baidu has said its new ERNIE X1 reasoning model “delivers performance on par with DeepSeek R1 at only half the price,” and has “stronger understanding, planning, reflection, and evolution capabilities.” CNBC has not been able to independently verify this claim.

According to Wei Sun, principal analyst of artificial intelligence at Counterpoint Research, Baidu’s future competitiveness could hinge on whether its new models deliver on the promised performance and cost advantages. 

“Baidu is clearly in catch-up mode, largely due to its slow innovation pace and underestimating rapid shifts in market dynamics,” Sun said. 

What happened? 

Baidu rolled out its first generative AI platform to the public in 2023, giving China one of its first answers to OpenAI’s popular AI chatbot ChatGPT. 

However, despite initial momentum, Baidu’s Ernie product has since been eclipsed by competitors including startups as well as large-tech companies such as Alibaba and ByteDance.

Experts list a number of reasons for Baidu’s struggles and slow rate of innovation.

“Baidu fell behind when they tried to build proprietary models and compete for funding for AI,” Ray Wang, principal analyst and founder of Constellation Research, told CNBC. He added that the company has also suffered from recent government crackdowns and was distracted by “regulatory nonsense.” 

CFOTO | Future Publishing | Getty Images

Proprietary models keep their source code and underlying architecture confidential, in contrast to models from the likes of DeepSeek, whose source code is made freely available on the open web for possible modification and redistribution.

“Using a closed-source approach means that [Baidu] was training its model from scratch whereas the open-source models were able to leverage certain parts that were communal to developers,” said Kai Wang, a senior equity analyst for Morningstar. 

Baidu, however, said last month that it would make its next-generation AI model Ernie open-source from June 30, according to Reuters.

“Baidu has always been very supportive of its proprietary business model and was vocal against open source, but disruptors like DeepSeek have proven that open source models can be as competitive,” said Omdia’s Su. 

He added that Baidu is “merely following the footstep” of its biggest competitors in China, namely Alibaba, DeepSeek, and Tencent, which have all now released open-source models. 

Baidu’s advantages

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