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最新 AI 资讯
As AI Cannabilises Revenue, Indian IT Looks to Cybersecurity for Margins
As generative AI automates coding, Indian IT firms are racing to build cybersecurity capabilities through acquisitions, partnerships and AI-native platforms.
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Accenture Wins NATO's Multi-Million-Euro Digital Infrastructure Contract
Accenture will work with Italian firm Leonardo to build a secure, cloud-enabled business network for NATO over seven years.
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![[Exclusive] Bengaluru Startup QpiAI Open-Sources Quantum SDK for Developers, Researchers](/_next/image?url=https%3A%2F%2Fteenyfy-assets.s3.us-east-1.amazonaws.com%2Ftemp_exclusive_54eb118d0e.jpg&w=750&q=75)
[Exclusive] Bengaluru Startup QpiAI Open-Sources Quantum SDK for Developers, Researchers
The quantum startup aims to expand access to quantum software and connect users to its quantum computers through QCloud.
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Jio Haptik Launches SOLO to Equip SMEs With AI Business Teams
The Reliance Jio-backed firm has introduced an AI tool aimed at solopreneurs, home businesses, and small enterprises across the country
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Perplexity is Building a Claude Code, Cursor Competitor: Report
Perplexity has reportedly been using the AI tool internally since May.
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After DeepSeek, Z.ai Explores Building AI Chip as GLM Demand Surges: Report
Z.ai is seeing rapid adoption of its GLM models as the Chinese AI company looks for reliable computing infrastructure.
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Meta Launches Muse Image AI Model With Web Search Feature, Previews Muse Video
Meta has also released Content Seal, an invisible watermark designed to help identify AI-generated images.
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OpenAI’s Codex Breakthrough Heralds a New Era in Chip Design
The company's use of agentic models to take its custom chip from a blank slate to tape-out in just nine months signals a new era of chip design.
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Discord admits AI moderation bug wrongfully banned users over harmless images
Discord has acknowledged that a bug in its AI moderation system mistakenly banned more than 8,000 users over the past two months, after harmless images—including spreadsheets, chessboards, game textures, as well as white and gray transparent backgrounds—were incorrectly flagged as harmful content. The company confirmed that the issue had been affecting accounts since May, with an additional 200 users banned over the weekend before its team identified and fixed the problem. All affected accounts are currently in the process of being restored. The incident highlights one of the growing challenges surrounding AI-assisted moderation as many platforms increasingly rely on automated systems to identify illegal or abusive material at scale. In adetailed thread on X, Discord explained that its automated safety system works by matching uploaded content against databases of known harmful material. While the technology is designed to catch illegal content, the company acknowledged that it can sometimes generate false positives. A human moderator reviews the content, but a bug caused the system to immediately ban affected accounts. “We’re working on better safeguards so this can’t happen again,” the company wrote. Our systems flag content by matching it against known harmful material. This kind of similarity matching can produce false positives, which is why a member of our Trust & Safety team always reviews flagged content before any action is taken.The intended behavior is to…— Discord Support (@discord_support)July 7, 2026 Our systems flag content by matching it against known harmful material. This kind of similarity matching can produce false positives, which is why a member of our Trust & Safety team always reviews flagged content before any action is taken.The intended behavior is to… Across X andReddit, users have claimed they had been permanently suspended simply for uploading images containing square grid patterns. Several users speculated that Discord’s AI moderation tools have become increasingly sensitive to grid-like patterns because they have previously been used in attempts to obscure or disguise NSFW and child exploitation content from automated detection systems. Affected users have been expressing frustration on social media, with some arguing that permanent account bans based solely on automated detection can have serious consequences, particularly for users who rely on Discord for work, gaming communities, or long-distance social connections. “Losing a Discord account to something as unfair as this can be extremely devastating and affect users severely, and every day millions of users are affected by false AI bans. This needs to be stopped,” one X userwrote. My account was wrongfully banned from your platform due to a bug in your AI automod detecting my GAME TEXTURES as CSAM. I need my account back as I’m a game director and use Discord for all my communication. I have requested a review of my suspension.@discord@discord_supportpic.twitter.com/QfAkCIJo6S— JDBRYANT 🎂 TODAY (@jdbryantdev)July 4, 2026 My account was wrongfully banned from your platform due to a bug in your AI automod detecting my GAME TEXTURES as CSAM. I need my account back as I’m a game director and use Discord for all my communication. I have requested a review of my suspension.@discord@discord_supportpic.twitter.com/QfAkCIJo6S Discord isn’t alone in facing moderation troubles due to automated systems. Last year, users ofInstagramandFacebook Groupsreported widespread unexplained account suspensions that many believed were caused by AI moderation systems. Although users pointed to automation as the likely culprit, Meta never publicly confirmed whether AI errors were responsible. Now Meta’s Oversight Board ispushing for increased transparency. Tumblr last year alsofaced complaintsfrom users who said their accounts had been mass-suspended without clear explanations.
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Microsoft joins AI cost-cutting trend by relying more on its own models
AsAI costs continue to rise, companies are looking for ways to cut back. The most recent example is Microsoft, which has reportedly begun to deploy a cost-savings strategy by relying less on software from OpenAI and Anthropic and instead deploying its own in-house models. Indeed, when it comes to two of its most widely used programs — Excel and Word — Microsoft has begun to use its homemadeMAI modelsto respond to a certain percentage of user prompts, BloombergreportedTuesday. In the past, the company had advertised the fact that large parts of Office 365 arepowered by models from both OpenAI and Anthropic. While Microsoft still relies on those third-party models, it has also increasingly sought to stand up its own AI agents. Last month, at its annual Build conference, the company announced thelaunch of seven new MAI models, including an agentic coder and a text-to-image generator. When reached for comment by TechCrunch, Microsoft said that it had nothing further to share. Microsoft’s apparent cutbacks are part of a broader trend. After a brief blitz of “tokenmaxxing” earlier this year, the last few months have seen a news cycle awash in stories about tech companies acting significantly more thrifty. Other large companies — likeAmazon,Uber,Meta, andAccenture— have also reportedly made moves to curb spending. The immense cost of providing and buying AI services has become a controversial part of the industry. The sticker shock has gotten so bad in some parts of Silicon Valley that some companiesare reportedlylooking to Chinese models for more affordable agentic solutions — despite some concerns overpotential security issues.
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Why the rise of open source AI isn’t hurting Anthropic … yet
On Monday, Decagon CEO Jesse Zhang published a provocative new theory, posted under the title“Everyone is wrong about open source AI in the enterprise.”The post grapples with one of the most interesting contradictions of today’s AI economy: More mature AI deployments are switching to lighter models, he says, even at his own company. But the overall spend on expensive state-of-the-art models has barely budged. It’s a new way to think about the relationship between frontier and open source models. In Zhang’s telling, they aren’t competitors, and open source models’ success isn’t coming at the expense of frontier labs. Instead, they’re two phases of the same life cycle, with expensive frontier models being used to prove out use cases that can be passed along to cheaper open source alternatives as they mature. As more mature use casesswitch to lighter models, new use cases keep arising — and the overall spend on frontier models barely goes down. Zhang doesn’t give much data to support the point, but the data isn’t hard to find.Vercel’s AI gateway dashboardshows that, in just the past week, DeepSeek has surged into the lead for token volumes, now processing just over a third of the tokens passing through the company’s infrastructure. Z.ai — the lab behind the popular GLM-5.2 model — jumped into a respectable fourth place over the same period. But if you scroll down to overall token spend, you’ll see Anthropic still accounts for more than half of the overall AI spend on the platform. Given that much of the recent change comes from Anthropic’s own rising prices, the share has dropped slightly over the past month, but not significantly. OpenRoutertells a similar story, capturing a much larger (but slightly less enterprise-y) segment of the market. DeepSeek V4 Flash is the main winner on overall usage, processing 5.3 trillion tokens weekly. The most popular frontier model, Opus 4.8, handles just over 2 trillion. OpenRouter doesn’t rank models by total spend, but it registers the average token cost for Opus 4.8 as roughly 23x higher than V4 Flash ($1.37 per million tokens, compared to just 6 cents), which would mean Opus was still probably capturing the lion’s share of spending. Those figures don’t even capture the newest arrival, Nvidia’s Nemotron, which ispoised to leap to the front of the packby virtue of Nvidia’s strong connections and the model’s own extreme adaptability. Those figures don’t fully prove Zhang’s point about the AI life cycles, but they do show frontier labs like Anthropic aren’t suffering too much from the rise of open source — at least not yet. One explanation is that the market of AI-addressable tasks is growing so fast that the top models are able to maintain their position just by dominating early-stage deployments. As Zhang puts it, “The frontier labs will keep owning discovery. Open source will increasingly own production.” Another explanation might be that, even as clients move to open source, many use cases are so difficult that they can’t be entirely replaced with cheaper alternatives. Either way, this two-tiered economy of models may become a relatively stable feature of the AI economy. As recently as last September, I was writing about the possibility that foundation labs would end upselling coffee beans to Starbucks— that is, serving as commodity inputs while the application layer reaped the benefits. Some parts of that prediction came true: Vertical AI plays switched to lighter models, for one, and the economics of “GPT wrapper” startups have remained mostly stable. But we’re also seeing that, token for token, frontier providers have been able to hold on to the most desirable part of the marketplace — the premium token price. And that doesn’t seem likely to change any time soon.
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Meta rolls out Muse, a new AI image generator
Metahas unveiledits new AI image generator, Muse Image, which was produced by Meta Superintelligence Labs, the company’s dedicated AI unit. The new feature, which was internally code-named Mango,will be availablefor free through the Meta AI app, as well as in Instagram Stories and WhatsApp. What exactly can you do with Muse? It sounds like the use-cases are similar to most other AI image generators — you’ll be able to create a whole lot of goofy and cartoonish images, for instance. If you’re suffering from a dearth of imagination and can’t come up with any original prompts on your own, Meta says that Muse comes with “presets” — prefabricated image prompts — to “spark ideas.” An accompanying video shows other potential uses. One is to use Muse tocreate custom ads(AI has notably crept into advertising over the past year) or to play around with interior decoration ideas (in the video, a user leverages Muse to see what a used couch might look like in their garage). This last function is designed to be integrated with Facebook Marketplace, Meta’s popular Craigslist-like locus of used furniture and accessories. The model also features prompt-based image editing, which can be used to create images to share across Meta’s various apps and platforms. “Ask it to mock up an image of you in front of a historical landmark, cleanly erase a photobomber from the background of a shot, or write a custom prompt to build a functional QR code,” the company offers. At the same time, Meta islaunching a host of new AI effectsfor Instagram Stories which are supported by Muse. Those effects include various customizable filters that can be used to modify existing photos. Meta says that the use of the new AI model is free for “everyday creation” although, past a certain limit, users will need to use Meta’s subscription plans. The company also said that Muse Video — presumably an AI video generator — is “already in development.” TechCrunch reached out to Meta for more information. Meta has released a number of AI apps and services over the past year, including an assistantcalled Creator, andPocket, an app that can be used to vibe code video games. The company has been accused of having anebulous AI strategy, although it’s stillon track to spend a whole loton AI infrastructure this year as it continues to build out its services.
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