Google said Friday that the company is expanding Gemini’s latest in-depth research mode to 40 more languages. The company launched the in-depth research mode earlier this month, allowing Google One AI premium plan users to unlock an AI-powered research assistant of sorts. The in-depth function works in a multi-step method, from creating a research plan […]
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In September, OpenAI unveiled a radically new type of AI model called o1. In a matter of months, rivals introduced similar offerings.
On Thursday, Google released Gemini 2.0 Flash Thinking, which uses reasoning techniques that look a lot like o1.
Even before that, in November, a Chinese company announced DeepSeek, an AI model that breaks challenging questions down into more manageable tasks like OpenAI's o1 does.
This is the latest example of a crowded AI frontier where pricey innovations are swiftly matched, making it harder to stand out.
"It's amazing how quickly AI model improvements get commoditized," Rahul Sonwalkar, CEO of the startup Julius AI, said. "Companies spend massive amounts building these new models, and within a few months they become a commodity."
The proliferation of multiple AI models with similar capabilities could make it difficult to justify charging high prices to use these tools. The price of accessing AI models has indeed plunged in the past year or so.
That, in turn, could raise questions about whether it's worth spending hundreds of millions of dollars, or even billions, to build the next top AI model.
When OpenAI previewed its o1 model in September, the product was hailed as a breakthrough. It uses a new approach called inference-time compute to answer more challenging questions.
It does this by slicing queries into more digestible tasks and turning each of these stages into a new prompt that the model tackles. Each step requires running a new request, which is known as the inference stage in AI.
This produces a chain of thought or chain of reasoning in which each part of the problem is answered, and the model doesn't move on to the next stage until it ultimately comes up with a full response.
The model can even backtrack and check its prior steps and correct errors, or try solutions and fail before trying something else. This is akin to how humans spend longer working through complex tasks.
In a mere two months, o1 had a rival. On November 20, a Chinese AI company released DeepSeek.
"They were probably the first ones to reproduce o1," said Charlie Snell, an AI researcher at UC Berkeley who coauthored a Google DeepMind paper this year on inference-time compute.
He's tried DeepSeek's AI model and says it performs well on complex math problems that must be solved by thinking for longer and in stages.
He noted that in DeepSeek's DeepThink mode, the model shows users every step of its thought process. With o1, these intermediate steps are hidden from users.
"I've asked people at OpenAI what they think of it," Snell told BI. "They say it looks like the same thing, but they don't how DeepSeek did this so fast."
OpenAI didn't respond to a request for comment. On Friday, the startup previewed an o1 successor, called o3. Francois Chollet, a respected AI expert, called the update a "significant breakthrough."
Andrej Karpathy, an OpenAI cofounder, praised Google's new "Thinking" model for the same reasoning feature.
"The prominent and pleasant surprise here is that unlike o1 the reasoning traces of the model are shown," he wrote on X. "As a user I personally really like this because the reasoning itself is interesting to see and read — the models actively think through different possibilities, ideas, debate themselves, etc., it's part of the value add."
Snell shared a multistep math problem with Business Insider, which we used to test DeepSeek for ourselves:
"Find a sequence of +, -, /, * which can be applied to the numbers 7, 3, 11, 5 to get to 24, where each of the given numbers is used exactly once."
BI put that prompt in DeepSeek's chat window on its website. The model responded initially by laying out the challenge ahead.
"Alright, so I've got this problem here: I need to use the numbers 7, 3, 11, and 5, and combine them with the operations of addition, subtraction, multiplication, and division, using each number exactly once, to get to 24," it replied. "At first glance, this seems a bit tricky, but I think with some systematic thinking, I can figure it out."
It then proceeded through multiple steps over roughly 16 pages of discussion that included mathematical calculations and equations. The model sometimes got it wrong, but it spotted this and didn't give up. Instead, it swiftly moved on to another possible solution.
"Almost got close there with 33 / 7 * 5 ≈ 23.57, but not quite 24. Maybe I need to try a different approach," it wrote at one point.
After a few minutes, it found the correct solution.
"You can see it try different ideas and backtrack," Snell said in an interview on Wednesday. He highlighted this part of DeepSeek's chain of thought as particularly noteworthy:
"This is getting really time-consuming. Maybe I need to consider a different strategy," the AI model wrote. "Instead of combining two numbers at a time, perhaps I should look for a way to group them differently or use operations in a nested manner."
Snell said other companies are likely working on AI models that use the same inference-time compute approach as OpenAI.
"DeepSeek does this already, so I assume others are working on this," he added on Wednesday.
The following day, Google released Gemini 2.0 Flash Thinking. Like DeepSeek, this new model shows users each step of its thought process while tackling problems.
Jeff Dean, a Google AI veteran, shared a demo on X that showed this new model solving a physics problem and explained its reasoning steps.
"This model is trained to use thoughts to strengthen its reasoning," Dean wrote. "We see promising results when we increase inference time computation!"
Over the past month, we've seen a rapid cadence of notable AI-related announcements and releases from both Google and OpenAI, and it's been making the AI community's head spin. It has also poured fuel on the fire of the OpenAI-Google rivalry, an accelerating game of one-upmanship taking place unusually close to the Christmas holiday.
"How are people surviving with the firehose of AI updates that are coming out," wrote one user on X last Friday, which is still a hotbed of AI-related conversation. "in the last <24 hours we got gemini flash 2.0 and chatGPT with screenshare, deep research, pika 2, sora, chatGPT projects, anthropic clio, wtf it never ends."
Rumors travel quickly in the AI world, and people in the AI industry had been expecting OpenAI to ship some major products in December. Once OpenAI announced "12 days of OpenAI" earlier this month, Google jumped into gear and seemingly decided to try to one-up its rival on several counts. So far, the strategy appears to be working, but it's coming at the cost of the rest of the world being able to absorb the implications of the new releases.
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It's been a really busy month for Google as it apparently endeavors to outshine OpenAI with a blitz of AI releases. On Thursday, Google dropped its latest party trick: Gemini 2.0 Flash Thinking Experimental, which is a new AI model that uses runtime "reasoning" techniques similar to OpenAI's o1 to achieve "deeper thinking" on problems fed into it.
The experimental model builds on Google's newly released Gemini 2.0 Flash and runs on its AI Studio platform, but early tests conducted by TechCrunch reporter Kyle Wiggers reveal accuracy issues with some basic tasks, such as incorrectly counting that the word "strawberry" contains two R's.
These so-called reasoning models differ from standard AI models by incorporating feedback loops of self-checking mechanisms, similar to techniques we first saw in early 2023 with hobbyist projects like "Baby AGI." The process requires more computing time, often adding extra seconds or minutes to response times. Companies have turned to reasoning models as traditional scaling methods at training time have been showing diminishing returns.
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Google has released what it’s calling a new “reasoning” AI model — but it’s in the experimental stages, and from our brief testing, there’s certainly room for improvement. The new model, called Gemini 2.0 Flash Thinking Experimental (a mouthful, to be sure), is available in AI Studio, Google’s AI prototyping platform. A model card describes […]
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Internal guidelines passed down from Google led to concerns that the AI model could be prone to inaccurate outputs on topics like healthcare.
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Google on Tuesday announced support for third-party tools in Gemini Code Assist, its enterprise-focused AI code completion service. Code Assist launched in April as a rebrand of a similar service Google offered under its now-defunct Duet AI branding. Available through plug-ins for popular dev environments like VS Code and JetBrains, Code Assist is powered by Google’s Gemini […]
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Gemini is Google’s long-promised, next-gen generative AI model family.
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On Wednesday, Google unveiled Gemini 2.0, the next generation of its AI-model family, starting with an experimental release called Gemini 2.0 Flash. The model family can generate text, images, and speech while processing multiple types of input including text, images, audio, and video. It's similar to multimodal AI models like GPT-4o, which powers OpenAI's ChatGPT.
"Gemini 2.0 Flash builds on the success of 1.5 Flash, our most popular model yet for developers, with enhanced performance at similarly fast response times," said Google in a statement. "Notably, 2.0 Flash even outperforms 1.5 Pro on key benchmarks, at twice the speed."
Gemini 2.0 Flash—which is the smallest model of the 2.0 family in terms of parameter count—launches today through Google's developer platforms like Gemini API, AI Studio, and Vertex AI. However, its image generation and text-to-speech features remain limited to early access partners until January 2025. Google plans to integrate the tech into products like Android Studio, Chrome DevTools, and Firebase.
Google’s next major AI model has arrived to combat a slew of new offerings from OpenAI. On Wednesday, Google announced Gemini 2.0 Flash, which the company says can natively generate images and audio in addition to text. 2.0 Flash can also use third-party apps and services, allowing it to tap into Google Search, execute code, […]
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Google's AI Overviews feature on Search is getting an upgrade, thanks to the company's newly launched Gemini 2.0 model.
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Google is bringing a new capability to Gemini, its chatbot platform, that enables the AI to perform 'deep research' on a subject.
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As Google pours untold amounts of cash into AI, it's banking on products such as Gemini for Google Workspace to turn that investment into revenue. An internal presentation reveals the company worried that Gemini lagged behind its rivals across key metrics.
Gemini for Google Workspace puts Google's AI features into a handful of the company's productivity tools, such as Gmail, Docs, and Google Meet. Users can have the AI model rewrite an email, whip up a presentation, or summarize documents filled with dense information. Google, which charges customers extra for these add-ons, claims the features will save users time and improve the quality of their work.
Gemini for Google Workspace trailed all its key rivals, including Microsoft, OpenAI, and even Apple, when it came to brand familiarity and usage, according to an internal market research presentation reviewed by Business Insider.
The data tracked Gemini's brand strength during the first half of 2024 and included data on what percentage of audiences use and pay for Gemini for Google Workspace in certain segments.
One document seen by BI said that Workspace's Gemini tools were "far behind the competition" but that a strong Q4 could help the company in 2025.
In a written statement, a spokesperson said the data came from a study tracking brand awareness during the brand transition from "Duet AI" to "Gemini" earlier this year and called the data "old and obsolete."
"In the time since, we've brought Gemini for Workspace to millions more customers and made significant, double-digit gains across key categories, including familiarity, future consideration, and usage. We're very pleased with our momentum and are encouraged by all the great feedback we are getting from our users," the spokesperson added.
The internal data tracked Gemini's brand strength across commercial, consumer, and executive groups. In the US commercial group, Gemini scored lower than Microsoft Copilot and ChatGPT across four categories: familiarity, consideration, usage, and paid usage, one slide showed. Paid usage was measured at 22%, 16 points lower than Copilot and ChatGPT.
Data for the UK in the commercial group also showed Gemini mostly behind its rivals, although it scored slightly higher than Copilot in paid usage. In Brazil and India, Gemini for Workspace fared better than Copilot across most categories but still fell below ChatGPT, the data showed.
"Gemini trails both Copilot and ChatGPT in established markets," the document said, adding that it "rises above Copilot across the funnel" in Brazil and India.
In another part of Google's internal presentation that focused on brand familiarity, Google's Gemini for Workspace came in last place in consumer, commercial, and executive categories, trailing ChatGPT, Copilot, Meta AI, and Apple AI.
Familiarity was particularly low for the US consumer category, with Gemini for Workspace scoring just 45%, while Copilot scored 49%, ChatGPT and Apple both scored 80%, and Meta scored 82%.
Microsoft's Copilot, which does similar tasks like summarizing emails and meetings, likewise struggles to live up to the hype, with some dissatisfied customers and employees who said the company has oversold the current capabilities of the product, BI recently reported.
"We have the same problem as Microsoft," said a Google employee directly familiar with the Gemini for Workspace strategy. "Just with less market share." The person asked to remain anonymous because they were not permitted to speak to the press.
Google's data showed Apple and Meta's AI products have much bigger market recognition, which could benefit those companies as they roll out business products that compete with Google's.
Internally, the Workspace group has recently undergone a reshuffle. The head of Google Workspace, Aparna Pappu, announced internally in October that she was stepping down, BI previously reported. Bob Frati, vice president of Workspace sales, also left the company earlier this year. Jerry Dischler, a former ads exec who moved to the Cloud organization earlier this year, now leads the Workspace group.
Are you a current or former Google employee? Got more insight to share? You can reach the reporter Hugh Langley via the encrypted messaging app Signal (+1-628-228-1836) or email ([email protected]).
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ChatGPT is gaining on Google in the lucrative online search market, according to new data released this week.
In a recent survey of 1,000 people, OpenAI's chatbot was the top search provider for 5% of respondents, up from 1% in June, according to brokerage firm Evercore ISI.
Millennials drove the most adoption, the firm added in a research note sent to investors.
Google still dominates the search market, but its share slipped. According to the survey results, 78% of respondents said their first choice was Google, down from 80% in June.
A few percentage points may not seem like much, but controlling how people access the world's online information is a big deal. It's what fuels Google's ads business, which produces the bulk of its revenue and huge profits. Microsoft Bing only has 4% of the search market, per the Evercore report, yet it generates billions of dollars in revenue each year.
ChatGPT's gains, however slight, are another sign that Google's status as the internet's gatekeeper may be under threat from generative AI. This new technology is changing how millions of people access digital information, sparking a rare debate about the sustainability of Google's search dominance.
OpenAI launched a full search feature for ChatGPT at the end of October. It's also got a deal with Apple this year that puts ChatGPT in a prominent position on many iPhones. Both moves are a direct challenge to Google. (Axel Springer, the owner of Business Insider, has a commercial relationship with OpenAI).
When the Evercore analysts drilled down on the "usefulness" of Google's AI tools, ChatGPT, and Copilot, Microsoft's consumer AI helper, across 10 different scenarios, they found intriguing results.
There were a few situations where ChatGPT beat Google on satisfaction by a pretty wide margin: people learning specific skills or tasks, wanting help with writing and coding, and looking to be more productive at work.
It even had a 4% lead in a category that suggests Google shouldn't sleep too easy: people researching products and pricing online.
Still, Google remains far ahead, and there were positive findings for the internet giant from Evercore's latest survey.
Earlier this year, Google released Gemini, a ChatGPT-like helper, and rolled out AI Overviews, a feature that uses generative AI to summarize many search results. In the Evercore survey, 71% of Google users said these tools were more effective than the previous search experience.
In another survey finding, among people using tools like ChatGPT and Gemini, 53% said they're searching more. That helps Google as well as OpenAI.
What's more, the tech giant's dominance hasn't dipped when it comes to commercial searches: people looking to buy stuff like iPhones and insurance. This suggests Google's market share slippage is probably more about queries for general information, meaning Google's revenue growth from search is probably safe for now.
So in terms of gobbling up more search revenue, ChatGPT has its work cut out.
Evercore analyst Mark Mahaney told BI that even a 1% share of the search market is worth roughly $2 billion a year in revenue. But that only works if you can make money from search queries as well as Google does.
"That's 1% share of commercial searches and assuming you can monetize as well as Google — and the latter is highly unlikely in the near or medium term," he said.
Google Labs, the experimental arm of the tech giant, has introduced a new online project that offers an entertaining variation of the game of chess. The web experiment is named GenChess, which, as the name implies, uses Gemini Imagen 3, Google’s image generation model, allowing players to customize their own chess pieces using text prompts. […]
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Google’s Gemini chatbot can now remember things like info about your life, work, and personal preferences. As flagged by posters on X (and Google’s official account), a “memory” feature has begun rolling out to certain Gemini users, including this reporter. Like ChatGPT’s memory, Gemini’s adds context to the current conversation. For example, tell Gemini to […]
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