Google Launches Gemini 2.0 Pro LLM
Google introduces Gemini 2.0 Flash Thinking, an AI model that enhances reasoning, accuracy, and integration with YouTube, Search, and Google Maps.
Google launched its much-anticipated new flagship AI model, Gemini 2.0 Pro Experimental, on Wednesday. The announcement was part of a series of other AI model releases. The company is also making its reasoning model, Gemini 2.0 Flash Thinking, available in the Gemini app.
Notably, Google is releasing these AI models as the tech world remains fixated on cheaper AI reasoning models offered by the Chinese AI startup DeepSeek. DeepSeek’s models match or surpass the performance of leading AI models offered by American tech companies. At the same time, businesses can access DeepSeek’s models through the company’s API for a relative steal.
Google and DeepSeek both released AI reasoning models in December, but DeepSeek’s R1 got a lot more attention. Now, Google may be trying to put its Gemini 2.0 Flash Thinking model in front of more eyes through its popular Gemini app. As for Gemini 2.0 Pro, the successor to the Gemini 1.5 Pro model Google launched last February, Google says that it is now the leading model in its Gemini AI model family.
Google accidentally announced the Gemini 2.0 Pro model’s release in the Gemini app’s changelog roughly a week ago. But this time, it’s for real. The company is releasing an experimental version of the model on Wednesday in its AI development platforms, Vertex AI and Google AI Studio. Gemini 2.0 Pro will also be available to subscribers to Gemini Advanced in the Gemini app.
Specifically, the new Gemini Pro model excels at coding and handling complex prompts, per Google, and it comes with better understanding and reasoning of world knowledge than any of the company’s previous models. Gemini 2.0 Pro can call tools like Google Search, and execute code on behalf of users.
More on Google’s Gemini 2.0 Large Language Model on TechCrunch
How To Make DeepSeek And TikTok American | Perplexity CEO Aravind Srinivas Explains His Business Strategy
Deirdre Bosa sits down with Perplexity Co-founder and CEO Aravind Srinivas to talk the startup's case for why they are the best positioned to take over TikTok's U.S. operations at a time when security concerns around Chinese-owned apps like TikTok and DeepSeek are on the rise.
Bruce Burke Participating In Forbes Entrepreneur Of Impact Competition
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LinkedIn Is Testing An AI Tool That Could Transform How People Search for Jobs
The company says artificial intelligence could help surface jobs that remain hidden from typical search queries.
LinkedIn is testing a new job-hunting tool that uses a custom large language model to comb through huge quantities of data to help people find prospective roles. The company believes that artificial intelligence will help users unearth new roles they might have missed in the typical search process.
“The reality is, you don’t find your dream job by checking a set of keywords,” the company’s CEO, Ryan Roslansky, told WIRED in a statement. The new tool, he says, “can help you find relevant jobs you never even knew to search for.”
LinkedIn gave WIRED a preview of the tool, which is currently being tested by a small group of users. Job searchers can enter queries such as “find me a role where I can use marketing skills to help the environment,” or “show jobs in marketing that pay over $100K.”
LinkedIn developed its own large language model, or “LLM”—the kind of AI that powers ChatGPT—to comb through its data and parse search queries. A regular search might only bring up openings based on their job title; the new tool can identify ones based on a deeper analysis of the job description, information about the company and its peers, and posts from across the site.
It can also show job seekers what new skills they might need to pursue in order to land a particular role. “We are really using LLMs throughout the entire stack of our search and recommender system, all the way from query understanding to retrieval to ranking,” says Rohan Rajiv, a director of product at LinkedIn.
More on LinkedIn’s LLM and AI job search on Wired
How Artificial Intelligence is Powering Payments | Greg Ulrich, Mastercard
How does a company as massive as Mastercard decide where to deploy AI? Instead of centralizing every AI initiative, Mastercard operates under a “hub and spoke” model — balancing centralized AI leadership with decentralized innovation across business units.
In this episode, a16z Partner Marc Andrusko chats with Mastercard’s Chief AI and Data Officer Greg Ulrich about Mastercard’s long history of using AI, the opportunities (and potential risks) associated with integrating generative AI into fraud detection, determining what tech to employ based on use cases, and the best advice he’s ever gotten.
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Hugging Face Clones OpenAI’s Deep Research In Less Than 24 Hours
Open source Deep Research proves that agent frameworks boost AI model capability.
On Tuesday, Hugging Face researchers released an open source AI research agent called "Open Deep Research," created by an in-house team as a challenge 24 hours after the launch of OpenAI's Deep Research feature, which can autonomously browse the web and create research reports. The project seeks to match Deep Research's performance while making the technology freely available to developers.
"While powerful LLMs are now freely available in open-source, OpenAI didn’t disclose much about the agentic framework underlying Deep Research," writes Hugging Face on its announcement page. "So we decided to embark on a 24-hour mission to reproduce their results and open-source the needed framework along the way!"
Similar to both OpenAI's Deep Research and Google's implementation of its own "Deep Research" using Gemini (first introduced in December—before OpenAI), Hugging Face's solution adds an "agent" framework to an existing AI model to allow it to perform multi-step tasks, such as collecting information and building the report as it goes along that it presents to the user at the end.
The open source clone is already racking up comparable benchmark results. After only a day's work, Hugging Face's Open Deep Research has reached 55.15 percent accuracy on the General AI Assistants (GAIA) benchmark, which tests an AI model's ability to gather and synthesize information from multiple sources. OpenAI's Deep Research scored 67.36 percent accuracy on the same benchmark.
More on Hugging Face’s Deep Research Clone on ARS Technica
Microsoft AI Tour | New York | Keynote
Power your AI transformation with an insightful keynote from Scott Guthrie, Executive Vice President, Cloud + AI Group at Microsoft, and other industry experts.
Wayne Rasanen’s Award Winning DecaTxt 3 | A One-Handed Keyboard
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Arvind Jain’s AI Startup Glean Reaches $100 Million Annual Recurring Revenue
Glean, a company that makes search chatbots and agents for businesses, said it achieved an annual recurring revenue of $100 million in its last fiscal year. That's up from hitting $50 million ARR, or the yearly value of last month's revenue, in 2024.
A company that began as "Google search for the workplace" has more than doubled its customer base in the past year alone and was most recently valued at $4.6 billion in a funding round that included Altimeter, Kleiner Perkins, Sapphire Ventures, and SoftBank Vision Fund 2. It has become a daily use product for hundreds of customers, including Databricks, Duolingo, and Plaid.
Glean is part of a select group of AI startups seeing fast-growing revenue and strong investor interest. Anysphere, the 3-year-old startup behind the AI coding assistant Cursor, recently was valued at $2.5 billion and hit $100 million in annual recurring revenue, The New York Times reported last month. The AI legal startup Harvey is raising a new round at a $3 billion valuation and was bringing in $50 million in annual recurring revenue as of December, The Information said.
Enterprise search has become a key battleground for a wide variety of businesses such as Google, Snowflake, and Dropbox. OpenAI last year bought an enterprise search startup that could help ChatGPT compete more directly with Glean.
Glean's business has grown as organizations grasp the enormous potential of artificial intelligence to provide quick productivity gains, Arvind Jain, Glean's founder and CEO, said. The company often sells to customers who are just getting their feet wet and buying their first pure AI software, Jain added.
He said they say, "'Can I just have an assistant like ChatGPT but something that is knowledgeable about my company, my employees, everything?' That's what Glean is."
More about Glean’s success in providing AI Agents on Business Insider
How Infrastructure Is Powering The Age Of AI | Ric Lewis | Smart Talks With IBM
Discover how infrastructure drives AI innovation in this insightful discussion with Malcolm Gladwell and Ric Lewis, SVP of Infrastructure at IBM. Learn how hardware capabilities enable the matrix math behind large language models and how AI is transforming industries—from banking to your local coffee shop.
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