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Últimas Noticias de IA
Accenture, Anthropic Launch Cyber.AI to Expedite Cybersecurity Operations
The solution automates complex cybersecurity processes, protecting expansive digital environments without adding manual effort.
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Humanoid Escorts Melania Trump, Greets Leaders in Bengali at White House Summit
In her address, the US First Lady urged governments and educators to adopt AI in education.
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Namma Yatri Parent Moving Tech Acquires Automicle to Expand Zero-Commission Mobility Model into Europe
The deal extends MTI’s community-led mobility model internationally, reinforcing its vision of open, city-first infrastructure for sustainable urban transport and driver dignity.
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Agentic AI Could Change Software Engineering Forever
Instead of developers writing every line of code, they now provide high-level specifications. AI agents take over from there.
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Apple Has 'Complete Access' to Google's Gemini Model; Can Create Smaller Models via Distillation: Report
Apple has been granted full access to Google's Gemini model, which allows the iPhone maker to do more with the AI model used on Android smartphones, according to a report. The Cupertino company will be able to use the Gemini AI model for distillation in its own data centres, which means it can create smaller models that can be used for specific purposes. These models could be more efficient, would run on a user's device, and would not require access to the internet.
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Yann LeCun Builds a World Model That Runs on a Single GPU
LeWorldModel can plan up to 48 times faster than some existing world models while maintaining competitive performance.
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Infosys Announces FY26’s Largest Acquisition at $465 Mn; Total Deals Reach 5
The company has also acquired Stratus, extending the spree that includes Versent, MRE Consulting and The Missing Link.
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Invention Engine Rewrites the Accelerator Playbook for Deep Tech
With smaller cohorts and operator-led guidance, the accelerator pushes founders to engage deeply with market realities rather than relying on theoretical frameworks.
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How AlphaFold is Driving India’s Life Sciences Industry
This allows companies like GSK and Sanofi to speed up R&D by 30-40 per cent, enabling faster identification of drug targets
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How Google Used High School Math to Deliver 8x Performance Boost on NVIDIA H100s
“All you had to do was pay attention to the polar coordinates lecture in [trigonometry], and you could have discovered a 6x reduction in KV cache memory.”
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Mercor competitor Deccan AI raises $25M, sources experts from India
As demand grows for training and refining AI models,Deccan AI— a startup supplying post-training data and evaluation work — has raised $25 million in its first major funding round, with much of that work carried out by an India-based workforce of experts. The all-equity Series A round was led by A91 Partners, with participation from Susquehanna International Group and Prosus Ventures. While frontier AI labs including OpenAI and Anthropic build core models in-house, much of the post-training work — from data generation to evaluation and reinforcement learning — is increasingly being outsourced as companies push to make systems reliable in real-world use. Deccan is emerging as one of a new set of startups serving that demand. Founded in October 2024, Deccan provides services ranging from helping models improve coding and agent capabilities to training systems to interact with external tools such as application programming interfaces (APIs), which connect AI models to software systems. The startup works with frontier labs on tasks such as generating expert feedback, running evaluations and building reinforcement learning environments, while also serving enterprises through products including its evaluation suite, Helix, and an operations automation platform. The work is also evolving as models move beyond text into so-called “world models” that better understand physical environments, including robotics and vision systems. Deccan’s customers include Google DeepMind and Snowflake, according to the company. It has onboarded about 10 customers and runs a couple of dozen active projects at any given time, founder Rukesh Reddy (pictured above) said in an interview. The startup, headquartered in the San Francisco Bay Area with a large operations team in Hyderabad, employs about 125 people and relies on a network of more than 1 million contributors, including students, domain experts, and PhDs. Around 5,000 to 10,000 contributors are active in a typical month, Reddy told TechCrunch. About 10% of Deccan’s contributor base has advanced degrees such as master’s and PhDs, though the share is higher among active contributors depending on project requirements, Reddy said. The market for AI training services hasexpanded rapidlyalongside the rise of large language models, with companies such asMeta-owned Scale AIand its rivalSurge AI, as well as startupsTuringandMercorcompeting to provide data labeling, evaluation, and reinforcement learning services. “Quality remains an unsolved problem,” Reddy said, adding that tolerance for errors in post-training is “close to zero” as mistakes can directly affect model performance in production. That makes post-training more complex than earlier stages, requiring highly accurate, domain-specific data that is harder to scale. The work is also highly time-sensitive, he said, with AI labs sometimes requiring large volumes of high-quality data within days, making it difficult to balance speed with accuracy. The sector hasfaced criticism over working conditions and pay, with large pools of gig workers often used to generate training data. Reddy said earnings on Deccan’s platform range from about $10 to $700 per hour, with top contributors earning up to $7,000 a month. Even as its customers are largely U.S.-based AI labs, most of Deccan’s contributors are based in India. Competitors such as Turing and Mercoralso source contractorsfrom the country, but operate across abroader set of emerging markets. Deccan chose to concentrate much of its workforce in India to better manage quality, Reddy said. “Many of our competitors go to 100-plus countries to find the experts,” he said. “If you have operations in just one country, it becomes far easier to maintain quality.” That approach highlights India’s current position in the global AI value chain — as a supplier of talent and training data rather than a developer of frontier models, which remain concentrated among a handful of U.S. companies and a few players in China. However, Reddy said Deccan has begun sourcing talent from a few other markets, including the U.S., for niche expertise in geospatial data and semiconductor design. Reddy said Deccan was built as a “born GenAI” company, in contrast to traditional data labeling firms that began with computer vision tasks. This means it has focused on higher-skill work from the outset. Deccan grew 10x over the past year and is now at a double-digit million-dollar revenue run rate, Reddy said, declining to share specifics. About 80% of its revenue comes from its top five customers, reflecting the concentrated nature of the frontier AI market, he added.
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The least surprising chapter of the Manus story is what’s happening right now
Okay, so the U.S. and China are locked in an all-out race to build the most powerful AI on the planet. Beijing is throwing billions at homegrown models, tightening its grip on the tech sector, and watching nervously as its best AI talentgravitates to U.S. companies. A Carnegie Endowment study published late last year found that 87 of the 100 top Chinese AI researchers at U.S. institutions in 2019 are still there. Yet Manus — one of China’s most buzzed-about AI startups — quietly relocated to Singapore and sold itself to Meta for $2 billion. Did anyone think there wouldnotbe a reckoning over this tie-up? As industry watchers know, Manus burst onto the scene in the spring of last year with a demo video showing an AI agent screening job candidates, planning vacations, and analyzing stock portfolios, and it cheekily claimed it outperformed OpenAI’s Deep Research. Within weeks, Benchmark — the consummate Silicon Valley venture firm — led a $75 million funding round at a $500 million valuation. That was surprising. (Senator John Cornyn had thoughts,tweetingat the time, “Who thinks it is a good idea for American investors to subsidize our biggest adversary in AI, only to have the CCP use that technology to challenge us economically and militarily? Not me.”) By December, Manus had millions of users and was pulling in over $100 million in annual recurring revenue. Then Meta came calling, and Mark Zuckerberg, who has staked the company’s future on AI, snapped it up for $2 billion. It’s worth noting that Manus didn’t just sell itself to an American buyer; it spent the better part of last year actively trying to operate outside China’s orbit. The company relocated its headquarters and core team from Beijing to Singapore, restructured its ownership, and after the Meta deal was announced, Metapledged to cut all tieswith Manus’s Chinese investors and shut down its operations in China entirely. By every measure, Manus was trying to make itself a Singapore company. But if that string of events raised eyebrows in Washington, you can only imagine that in Beijing, they were apoplectic. China has a phrase for all of this: “selling young crops” — homegrown AI companies that move abroad and sell themselves to foreign buyers before they’ve fully matured, taking their intellectual property and talent with them. Beijing hates it and has spent years establishing that no company operates outside its reach. Surely, we all remember that time Jack Ma gave a speech in 2020, mildly criticizing Chinese regulators, after which he disappeared from public life for months, Ant Group’s blockbuster IPO was killed overnight, and Alibaba was handed a $2.8 billion fine. China then spent the next two years methodically dismantling its own booming tech sector, wiping out hundreds of billions in market value. Chinese leaders are many things, but subtle is not one of them. Which is why it wasn’t entirely surprising when, on Tuesday, the Financial Times reported that Manus co-founders Xiao Hong and Ji Yichao were summoned to a meeting this month with China’s National Development and Reform Commission and told that theywouldn’t be leaving the countryfor a while. No formal charges have been filed — just an inquiry into whether the Meta deal violated Beijing’s foreign investment rules. Beijing is calling it a routine regulatory review. At some point, someone at Manus probably thought they’d gotten away with it, and maybe they still will. But given the stakes of the AI race, that was always a big gamble. Now Beijing wants answers; Manus’s founders are apparently not going anywhere until it gets them.
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