最新 AI 资讯
Irish Enterprise Software Co Octave to Scale Hyderabad Tech Centre to 2,000 Engineers
The Hyderabad centre will serve as one of Octave’s global technology and innovation hubs.
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InspeCity Raises ₹100 Crore to Take In-Space Servicing Systems to Orbit
The funding will support four orbital missions and the commercial deployment of propulsion and inspection systems over 12–18 months.
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From Scans to Care: AI Rewrites India’s Diagnostic Playbook
AI is pushing India’s diagnostics beyond one-off reports towards personalised, continuous health monitoring.
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India’s Cybersecurity Startups Have VC Attention. Now Investors Want Proof
Investors are broadly bullish on India’s ability to produce global cybersecurity companies, but say distribution and trust remain major challenges
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Keysight Cuts AttoTude IC Design Cycles by More Than 50%
AttoTude has reduced chip design cycles to under six weeks while achieving first-pass silicon success.
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Why State Incentives Alone are Not Enough for GCCs to Scale in India
For many GCCs, the challenge is not growing in headcount but growing in responsibility and ownership.
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Amazon to Deploy 2 Mn NVIDIA GPUs for AI Data Centres
The deal will also bring NVIDIA’s Vera CPUs, NVLink Fusion and physical AI technologies to AWS infrastructure, while supporting government and enterprise AI workloads.
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WACKER Sets Up Pune GCC With HCLTech for Engineering and Digital Transformation
Under the collaboration, HCLTech will help build and scale the GCC’s technology workforce and strengthen its operational capabilities.
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NVIDIA’s AI Boom is Now Eating Into Its Own Memory Supply
NVIDIA expects soaring memory costs to hit margins as it commits billions to secure future supply.
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Plaud’s new earphones come with an eSIM-enabled case for talking to AI agents
Hardware companies have realized that note-taking is one of the easiest AI use cases to build for, and consequently have been busy shoving mics into everything from pendants and rings to credit-card-sized pucks and wristbands. Still, despite the variety of devices, only a few companies have been able to stand out. One of these companies is Plaud, which has over 2.5 million people using its hardware or software. It is now launching a note-taker in a new form factor: earphones. Called Plaud One, these adopt the simple bare-bones style of Apple’s Airpods, and can record calls, while their case can be used to record in-person conversations or take notes. Plaud isn’t the first to this form factor. Its rivals Viaim and Anker already have similar note-taking earbuds in the market. But the company is betting on its software and AI chops to set these apart. Plaud said that once the earbuds transcribe your conversation, its AI agent — which can connect to tools like Gmail, Google Calendar, Notion and Slack — can do things like writing follow-up emails and creating documents or presentations based on the contents of the conversation. By itself, that isn’t a unique pitch. Software note-takers like Granola, Fathom and Read AI have been offering similar workflow automation for a while now, transcribing calls and conversations, and allowing you to subsequently get an AI agent to do various tasks. The Plaud One takes that a step further, though, with its case, which supports an eSIM card. That feature, the company says, allows users to instruct Plaud’s AI agents remotely without using their phone or computer. The Plaud One has 12mm drivers and features active noise cancellation. The company says the case can capture voices clearly within a range of five meters, and the earphones can record six hours of in-person meetings and three hours of calls on a single charge. Combined with the case, users can record up to 25 hours of conversations on a single charge. Buyers get 300 minutes of free transcription per month, after which they will need to buy additional plans, which start from $8.33 per month (paid annually). That said, this launch seems to be more of a trial run. The Plaud One will be limited in quantity, as the startup likely wants to gauge demand for such AI-focused earphones before it commits to the format. Plaud is also working on building agentic capabilities, which is expected to arrive as part of an update in the coming months. The company says it will introduce a credit-based system for different tasks, and buyers of the Plaud One will get $200 in credits for these tasks. The company has had a good run so far, claiming in June that ithad reached annual run-rate revenue of $100 million. However, competition in the market is intense, with new hardware note-takers releasing every week. Its rival,YC-backed Pocket, has also reached that milestone, and tons of other companies likeAnker, Comu, Viaim, and software startup Gensparkare building in the space. Plaud’s CEO Nathan Xu holds that there should be an interface to talk to AI to invoke it from anywhere, and earbuds meet that need. “[For AI] we need to have a wearable and an always-ready interface, one that people love to wear, is socially acceptable and private by design,” he said in a briefing. Still, the company may find it challenging to draw people away from using their AirPods, Google Pixel Buds, Samsung Galaxy Buds, or wireless earbuds from any number of audio companies, which can pretty much do the same job when paired with any note-taking app. But Xu says Plaud is not necessarily competing against these companies, but positioning its meeting-recording tech to adopt a popular wearable format. Users can pre-order the device now for $249, and it will ship in the fourth quarter of 2026.
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Here’s all the times AI has gone rogue and hacked other companies
In July, OpenAI admitted that one of its agents tasked with completing a cybersecurity experimentbroke out of containment and hackedAI dataset platform Hugging Face. That incident, which gota full accounting from OpenAIyesterday, was the first publicly reported case where an LLM went rogue and autonomously hacked a third party. Since then, that unprecedented sci-fi-esque event turned out to be far less rare than anyone would hope for. According to a satirical website calledFelony Bench(for benchmark), which tallies these incidents, there have been 17 incidents in total. It’s important to remember that criminal law experts are not entirely sure whether the AI companies that made the LLMs that did the hacking can be prosecuted, nor whether the victims can sue them. Butwe are likely going to get an answer to those questions soon. Anthropic and OpenAI models lead the race with eight incidents each, and Meta trails behind with one, according to the site. At this point, it has become clear thatAI safety tests are becoming safety risks themselves. And some AI companies and workers themselves have recognized those risks in the “Pacing the Frontier” open letter, which called for developing AI capabilities responsibly. We decided it would be a good time to recap all these incidents chronologically. In this incident, OpenAI was running “an internal evaluation” of a model with “maximal cyber capabilities.” The plan was to have it solve a cybersecurity challenge in an environment with no internet access. Instead of solving the challenge, the model found an unknown vulnerability to escape the sandbox and gained internet access. From there, several agents worked together to target and hack HuggingFace thinking they could find the solution to the challenge there. OpenAI only found out after HuggingFacedisclosedit had been a victim of a fully autonomous attack. Whoops. OpenAI’s disclosure piqued the curiosity of Anthropic, who wondered: could this have happened to us too? Turns out, the answer was yes. Three times yes.The frontier lab discoveredthat its own models breached three different and still unnamed companies, with the earlier incident dating back to April — more than three months before the company discovered it. Anthropic partially blamed Irregular, a startup that runs AI cyber evaluations. Whoops. Once OpenAI started investigating the Hugging Face breach, it found out that the agents that hacked Hugging Face also broke into four accounts and four different companies,as Reuters first reported. Modal,an AI inference startup, was one of the victims. Whoops. In late July, Irregulartold OpenAIthat one of its models that was participating in a Capture-the-Flag competition — essentially a cybersecurity game where players hack systems designed specifically for the competition — escaped the game, connected to the internet, and hacked a real company. The reason? Irregular had given one of the fictional targets the same name of a real company. Whoops. Also in late July, the UK government’s AI Security institute, a public body tasked with researching the safety and risks of AI technologies,disclosedthat it detected several incidents involving both OpenAI and Anthropic models that while running “routine” evaluations targeted “real people and organisations.” In these cases, AISI had given the models internet access. Whoops. The good news is that the agency actually detected as they happened, rather than weeks later like in other incidents. In early August, Meta became the last company to disclose an incident involving one of its LLMs, which hacked “a third-party” service. Metablamed the incidenton a misconfiguration by Irregular, which was running a cybersecurity valuation for the tech giant that was supposed to not have internet access. Whoops. An Australian man asked an Anthropic AI agent to help him book a gym class, which he was on a waiting list for. “I was just sitting on the couch thinking, ‘Gee, this is a chore,’” the man told ABC Australia. In its attempt to comply with the request, the agentfound a vulnerability in the gym’s booking software, exploited it, and kicked out people who were ahead of the man on the waitlist. The man tried to undo the damage, asking the agent to undo its actions. The agent replied: “Bad news — I can’t add them back.” Whoops.
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AI’s memory crunch is coming for Android apps
Google is making changes to its requirements for Android apps as developers face industrywide memory chip shortages driven by the AI data center boom. This week, the tech giantannouncedtwo new app quality requirements, one of which is focused onreducing apps’ memory usageand optimizing its code. The company explains that the mobile industry is now facing “significant hardware supply constraints that are altering device memory availability,” which can then, in turn, affect the consumer’s experience with their devices. To address this, Google is now establishing new performance thresholds across several areas, like dynamic memory usage and bitmap usage. In addition, Google is adding code optimization requirements designed to prevent things like app slowdowns and crashes related to performance. To aid developers, the company is rolling out new tools that will alert them when their apps exceed the new thresholds so they can take action by optimizing their code. More diagnostic tools will arrive later in the year, Google noted, including deeper insights provided by aMemory Limiterfeature that prevents apps from using too much device memory. The changes are meant to help Android app and game makers continue to deliver a quality experience, Google says, while reflecting a market where memory may not be as widely available, particularly for low-end devices where price points are a concern. Developers have until February 2027 to meet the new thresholds, documented on Google’s Android Developer site. In addition, the company will require all Play Store apps to meet theZero Tap Sign-In requirementduring devicemigrationsby April 2027. This standard requires that apps with user sign-ins, whether optional or mandatory, automatically restore the user’s sign-in state when they move between Android devices using theAndroid Restore Credentials API.
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