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最新 AI 资讯
AI That Solves for India Can Solve for the World: Google DeepMind's Manish Gupta
The consensus is that generative artificial intelligence (AI) exploded into the mainstream with OpenAI's launch of ChatGPT in November 2022. But those who have followed this space closely know that it all began with a paper titled “Attention Is All You Need,” written by a team of eight researchers at Google Brain (now part of DeepMind) in 2017. The paper introduced the transformer architecture, a foundational neural network used in the Generative Pre-trained Transformer (GPT) by OpenAI and the backbone of all the company's frontier AI models ever since.
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Google Improves AI-Powered Shopping Experience in India With Gemini, Search, and Circle to Search Updates
Google announced a new set of AI-powered shopping features in India on Tuesday. The Mountain View-based tech giant is integrating its Gemini models with the extensive Shopping Graph, with the aim of simplifying product discovery. Updates have been introduced across the Gemini app, AI Mode in Search, and Circle to Search to help users browse, compare, and purchase products more efficiently. The company also noted that its Shopping Graph now includes over 50 billion products, with nearly 2 billion listings updated every hour.
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Google quietly launched an AI dictation app that works offline
Update (April 7,10:30 PM PT):The company has updated the app store listing and removed references to the Android app. But it also added that the iOS keyboard is coming soon. Google on Monday quietly released an offline-first dictation app called“Google AI Edge Eloquent” on iOSto take on the likes ofWispr Flow,SuperWhisper,Willow, and others. The app is free to download, and once its Gemma-based automatic speech recognition (ASR) models are downloaded, you can start dictating on your phone. In the app, you can see the live transcription, and when you hit pause, the app automatically filters out filler words like “um” and “ah” and polishes the text. Below the transcript are options like “Key points,” “Formal,” “Short,” and “Long” to transform the text. You can also turn off the cloud mode to use local-only processing. (When cloud mode is on, the app uses cloud-based Gemini models for text cleanup.) The Google AI Edge Eloquent can import certain keywords, names, and jargon from your Gmail account, if desired. Plus, you can add your own custom words to the list. The app displays the history of the transcription session and lets you search through all of them as well. It can show you words dictated in the last session, your words-per-minute speed, and the total number of words spoken. “Google AI Edge Eloquent is an advanced dictation app engineered to bridge the gap between natural speech and professional, ready-to-use text. Unlike standard dictation software that transcribes stumbles and filler words verbatim, Eloquent utilizes AI to capture your intended meaning. It automatically edits out ‘ums,’ ‘uhs,’ and mid-sentence self-corrections, outputting clean, accurate prose,” the company’s App Store description reads. While the app is currently only available on iOS, the App Store description references an Android version. (We have reached out to Google for more information and will update the story if we hear back.) According to the description, Eloquent offers “seamless Android integration,” where it can be set as users’ default keyboard for system-wide access across any text field. Plus, the app will be able to use the floating button feature,similar to the one Wispr Flow uses on Android, for easy access to transcription from anywhere. AI-powered transcription apps aregaining popularity among usersas speech-to-text models get better. With this experimental app,Google is joining the trend. If this test is successful, we could see improved transcription features across Android, too.
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IT, IITs, and GCCs: The Trifecta Fuelling India’s Next AI Innovations
The partnerships between IITs and GCCs focus on accelerating emerging AI and robotics innovations from academic research into real-world enterprise deployments.
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Zhipu AI’s GLM-5.1 Becomes Top Model on SWE-Bench Pro, Beats GPT-5.4, Claude Opus 4.6
The Chinese AI model was only trained on 100,000 Huawei Ascend without relying on NVIDIA chips.
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Intel Shares Rise by 4% After Joining Tesla’s Terafab Chip Venture
The partnership with Tesla, SpaceX, and xAI positions Intel at the centre of a $25 billion semiconductor project.
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AWS Summit Bengaluru Returns with a Focus on AI, Data & Cloud
The two-day event will feature keynote addresses, breakout sessions, hands-on labs, and an expo floor showcasing AWS technologies and partner solutions.
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The New Teddy Bear: Children Love AI Toy Robots, But Do They Have a Hidden Cost?
AI robots are transforming childhood experiences, but psychologists and policy experts caution against overdependence and data risks.
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Anthropic Unveils Claude Mythos, Says Model Too Dangerous to Launch
Anthropic said the model has already identified “thousands of high-severity vulnerabilities,” including flaws in major operating systems and web browsers.
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Uber to Use AWS Chips for Trip Processing and AI Training
Uber said its AI models are trained on data from billions of trips and deliveries.
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I can’t help rooting for tiny open source AI model maker Arcee
Arcee, a tiny 26-person U.S. startup that built a massive, 400B-parameter open source LLM ona $20 million shoestring budget, has released its new reasoning model. Arcee calls the model Trinity Large Thinking — and it’s the most capable open-weight model “ever released by a non-Chinese company,” claims CEO Mark McQuade to TechCrunch. As that comment implies, Arcee has a goal that I can’t help but root for: It wants to give U.S. and Western companies a model that gives them no reason to use a Chinese-based one. While Chinese models are extremely capable, they areperceived as risky, putting power, and perhaps data, into the hands of a government that doesn’t share all of the Western world’s ideals. With Arcee, companies can download the model, train it to their own needs, and use it on premises. Companies can also use Arcee’s cloud-hosted version, accessible via API. While Arcee’s models are not outperforming the closed source models from the big labs like Anthropic or OpenAI, they’re not being held hostage by the whims of those giants, either. For instance, Claude, with its exceptional abilities to code, has been a popular choice for users of open source AI agent tool OpenClaw. But Anthropic pulled the rug out from them last week when it told users that their Anthropic subscriptionswill no longer cover OpenClaw usage— they will have to pay additionally for that. (In February, OpenClaw creator Peter Steinberger said he wasjoining Anthropic’s biggest rival, OpenAI.) In contrast, McQuade proudly points todata from OpenRouterthat says it has become one of the top models used with OpenClaw. So, how good is Trinity Large Thinking? It is comparable to some of the other top open source models, according to the benchmark results it shared with TechCrunch. As we previously reported, it is not a head-to-head threat to the big cheese among U.S.-built open models: Meta’s Llama 4. But it also doesn’t have the odd, not-reallyopen source license issuesof Meta’s model. All of Arcee’s Trinity models are released under the gold standard for OS licenses, Apache 2.0. Just to be clear, there are also countless other U.S. startups offering open source models and, as a fan of the ingenuity of startups, I’m rooting for them, too.
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Uber is the latest to be won over by Amazon’s AI chips
On Tuesday, Amazonannouncedthat Uber was expanding its contract for AWS cloud services to run more of its ride-sharing features on Amazon’s chips. Uber will particularly expand its use of AWS’s Graviton (a low-power, ARM-based server CPU) and start a new trial testing Trainium3, AWS’s Nvidia competitor AI chip. This deal is a bit less about a long-term threat to Nvidia than it is a thorough thumbing of the nose by Amazon at AWS’s cloud competitors, Google and Oracle. While Uber historically ran its own data centers, back in 2023, the ride-hailing company famously signed giant, multi-year cloudcomputing deals with Oracle and Google. The idea was to move the majority of its IT infrastructure off its own data centers and onto these two clouds, it said. Even in December, Uber publicly reiterated that goal, writing ina blog post: In February 2023, Uber began transitioning from on-premise data centers to the cloud using OCI and Google Cloud Platform, taking on the dual challenge of shifting massive workloads and introducing Arm-powered compute instances into a previously x86-dominated environment. Uber particularly called out in that post the use of the ARM chips made by Ampere in Oracle’s cloud. This is where things get interesting. If you want a crash course in how inter-tangled Silicon Valley can be,take a look at the history of Ampere. Ampere was founded by former Intel bigwig Renee James after she was not promoted to CEO at the chipmaker. She pulled all her strings, including her power at her then-job as an investor at private equity firm Carlyle and her board seat position at Oracle, to raise the cash to start this company. Oracle owned about one-third of the company, and James had to give up her status as an independent Oracle director because of that investment. (James was, by the way, a key board personwho helped vote in Oracle’s $9.3 billion purchase of NetSuitein 2016, a company where Larry Ellison was a major stockholder. That dealsparked an unsuccessful shareholder lawsuitalleging Oracle overpaid for it.) In December, Ampere’s major competitor SoftBank acquired it, and Oracle sold its stake for ahandsome $2.7 billionpre-tax gain. James left Oracle’s board at the end of 2024 and is no longer working at Ampere. Oracle israising money as fast as it can to build data centersfor OpenAI and Stargate.Ellison said Oracle sold Amperebecause he believed designing chips in-house for its data centers was no longer a competitive advantage. It prefers to buy the chips and has signed massive deals with Nvidia. It’s worth noting that Oracle, SoftBank, and Nvidia are also part of OpenAI’sorbit of circular dealsthat are supposed to fund the model maker’s massive data center build-out. But now AWS is announcing it has nabbed a bigger contract from one of Oracle’s star customers, Uber, because it has in-house-designed chips. Uber joins Anthropic, OpenAI, and Apple as Big Tech companies that have signed on or increased their usage of AWS because of these AI chips. In December, Amazon CEO Andy Jassy saidTrainium was already a multibillion-dollar business. (Fora look at the team and lab that design these chips, check out our exclusive tour of the facility.)
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