Trump's Crackdown on Foreign Students Threatens to Disrupt Pipeline of Inventors
Ajay Bhatt had never been on a plane when he left India for City University of New York to pursue a graduate degree in 1981. More than four decades and 130 patents later, billions of people are still using Bhatt's most-recognizable invention, the Universal Serial Bus, or USB.
'My dad really didn't want me to go,' Bhatt recalls. But, he said, 'This was the country where you could get the very best education, and everybody was welcoming.'
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Android Authority
an hour ago
- Android Authority
Power station deal: The GRECELL T300 is just $121.49 right now!
Edgar Cervantes / Android Authority I got to test the GRECELL T300 Portable Power Station, and I must say it is one of my favorite options in terms of portability. It's still pretty portable and easy to carry, but it offers much more power than your typical power banks. It's also cheaper, especially today. You can take the GRECELL T300 home for just $121.49. Buy the GRECELL T300 Portable Power Station for just $121.49 ($48.50 off) This offer is available from Amazon. You must keep in mind that max savings can only be had by using two on-page coupons. First, apply the $40 discount, then click Redeem on the extra 5% coupon. This is the most portable power station we have tested, making it an excellent option for those who want a battery they can truly take around on their adventures. It weighs only 8.25 pounds, and measures in at 9.6 x 6.7 x 6.9 inches. It comes with a 230.8Wh battery capacity. To put this into perspective, that's enough to charge a phone about 25 times, or a laptop about 6 times. It can do much more than that, though. It has a max stable output of 330W, with support for 600W surges. This means it can also run more power-hungry things like a mini fridge, or even some TVs. Edgar Cervantes / Android Authority It comes with plenty of ports, including an AC outlet, two USB-C ports, two USB-A connections, and a car socket. The AC outlet is the only one that can reach the maximum 330W. One USB-C port can handle 60W, the other 18W, and both USB-A ports max out at 18W. Extra features include the addition of a very handy flashlight. And if you need to go off-grid for a bit, it supports an optional 40W solar panel. If you're looking for a portable battery that can do more than simple battery packs, and is at a good price, this is your best bet! I mean, considering today's discount, this price isn't much higher than many less capable power banks!
Associated Press
an hour ago
- Associated Press
Meta invests in AI firm Scale and recruits its CEO for 'superintelligence' team
Meta said Thursday it is making a large investment in artificial intelligence company Scale and recruiting its CEO Alexandr Wang to join a team developing 'superintelligence' at the tech giant. The move reflects a push by Meta CEO Mark Zuckerberg to revive AI efforts at the parent company of Facebook and Instagram as it faces tough competition from competitors such as Google and OpenAI. Meta announced what it called a 'strategic partnership and investment' with Scale late Thursday but didn't disclose the financial terms of the deal. Scale said the added investment puts its market value at over $29 billion. It won't be the first time a big tech company has gobbled up talent and products at innovative AI startups without formally acquiring them. Microsoft hired key staff from startup Inflection AI, including co-founder and CEO Mustafa Suleyman, who now runs Microsoft's AI division. Google pulled in the leaders of AI chatbot company while Amazon made a deal with San Francisco-based Adept that sent its CEO and key employees to the e-commerce giant. Amazon also got a license to Adept's AI systems and datasets. Wang was a 19-year-old student at the Massachusetts Institute of Technology when he and co-founder Lucy Guo started Scale in 2016. They won influential backing that summer from the startup incubator Y Combinator, which was led at the time by Sam Altman, now the CEO of OpenAI. Wang dropped out of MIT, following a trajectory similar to that of Meta CEO Mark Zuckerberg, who quit Harvard University to start Facebook more than a decade earlier. Scale's pitch was to supply the human labor needed to improve AI systems, hiring workers to draw boxes around a pedestrian or a dog in a street photo so that self-driving cars could better predict what's in front of them. General Motors and Toyota have been among Scale's customers. What Scale offered to AI developers was a more tailored version of Amazon's Mechanical Turk, which had long been a go-to service for matching freelance workers with temporary online jobs. More recently, the growing commercialization of AI large language models — the technology behind OpenAI's ChatGPT, Google's Gemini and Meta's Llama — brought a new market for Scale's annotation teams. The company claims to service 'every leading large language model,' including from Anthropic, OpenAI, Meta and Microsoft, by helping to fine tune their training data and test their performance. It's not clear what the Meta deal will mean for Scale's other customers. Wang has also sought to build close relationships with the U.S. government, winning military contracts to supply AI tools to the Pentagon and attending President Donald Trump's inauguration. The head of Trump's science and technology office, Michael Kratsios, was an executive at Scale for the four years between Trump's first and second terms. Meta has also begun providing AI services to the federal government. Meta has taken a different approach to AI than many of its rivals, releasing its flagship Llama system for free as an open-source product that enables people to use and modify some of its key components. Meta says more than a billion people use its AI products each month, but it's also widely seen as lagging behind competitors such as OpenAI and Google in encouraging consumer use of large language models, also known as LLMs. It hasn't yet released its purportedly most advanced model, Llama 4 Behemoth, despite previewing it in April as 'one of the smartest LLMs in the world and our most powerful yet.' Meta's chief AI scientist Yann LeCun, who in 2019 was a winner of computer science's top prize for his pioneering AI work, has expressed skepticism about the tech industry's current focus on large language models. 'How do we build AI systems that understand the physical world, that have persistent memory, that can reason and can plan?' LeCun asked at a French tech conference last year. These are all characteristics of intelligent behavior that large language models 'basically cannot do, or they can only do them in a very superficial, approximate way,' LeCun said. Instead, he emphasized Meta's interest in 'tracing a path towards human-level AI systems, or perhaps even superhuman.' LeCun co-founded Meta's AI research division more than a decade ago with Rob Fergus, a fellow professor at New York University. Fergus later left for Google but returned to Meta last month after a 5-year absence to run the research lab, replacing longtime director Joelle Pineau. Fergus wrote on LinkedIn last month that Meta's commitment to long-term AI research 'remains unwavering' and described the work as 'building human-level experiences that transform the way we interact with technology.'
Forbes
an hour ago
- Forbes
Why Most Startups Are Torching Their Marketing Spend
Every startup pitch sounds the same. Every sales email feels like it came from the same script. Every product demo promises to be 'AI-powered,' 'blazing fast,' and 'revolutionary.' That's because, in many cases, they were- thanks to generative AI tools like ChatGPT. AI was supposed to give companies a competitive edge. Instead, it triggered a conformity crisis—flattening differentiation and flooding the market with lookalike messaging. And that sameness is expensive. According to Rakuten Marketing, companies waste 26% of their marketing budgets—about $130 billion annually—on efforts that don't drive results. Sales teams aren't faring much better. Bloated prospect lists, recycled messaging, and unclear value props are dragging down deal cycles. Companies are pouring time and salaries into outreach strategies that barely move the needle—dozens of reps chasing the same stale leads with the same tired scripts. Customer acquisition costs are rising across nearly every sector, yet many teams keep expanding headcount instead of rethinking the model. The shift is already underway: 'The most effective teams are cutting through the noise—not by scaling up effort, but by scaling up precision,' according to Zach Vidibor, CEO and Co-founder of Octave. With AI handling the heavy lifting—identifying real buyer intent, automating workflows, and tailoring outreach—teams are closing more with less. But two startups: Clay and Octave are rewriting the rules. Clay, backed by Sequoia and now valued at $1.3 billion, is betting on signal-based sales. Instead of guessing who might be interested, Clay tracks over 100 real-time data points—like job changes, funding rounds, or new tech adoption—to tell companies when someone is actually ready to buy. It's the difference between cold outreach and timely engagement. In one example, Rippling used Clay to build over 50 workflows that replaced mass emailing with high-signal targeting. The result? A 30% response rate from a small number of qualified leads and triple the pipeline with 90% less noise. If Clay solves for "who," Octave solves for "what." Founded by GTM veteran Zach Vidibor (ex-LinkedIn, Dropbox, DocuSign), Octave uses AI to test dozens of message variants in parallel—helping companies learn what actually converts. "AI-powered" vs. "human-first." "Revolutionary" vs. "reliable." Instead of guessing which messaging resonates, Octave helps companies discover the phrasing that fits their specific customers, not just market trends. A SaaS company in the business travel space was competing in an increasingly crowded market. Rather than using generic pitches, they deployed Octave to personalize messaging for every prospect interaction. Their sales reps receive customized talking points before each call, powered by AI agents that research prospects and match them to relevant value propositions and use cases. The company has integrated Octave directly into Salesforce and calls their agents thousands of times per week. The financial results were clear: more demos booked, faster sales cycles, higher close rates. Their go-to-market engine finally matched the velocity of their competitive landscape. Vidibor's approach reflects a broader shift in how companies compete. When product features can be replicated quickly, the sustainable advantage lies in how fast you can test and adapt your messaging. The companies winning today aren't just building better products—they're optimizing their narrative faster than competitors can copy their innovations. In markets where everyone has access to similar tools, speed of message iteration becomes a critical differentiator. Success goes to companies that can reshape their story faster than others can replicate their features. This isn't just a marketing story—it's an economic one. When every company sounds the same, buyers can't tell the difference. That drags out decisions, drives up costs, and pushes even strong products into obscurity. The startups solving this problem aren't just improving efficiency. They're giving companies a way to stand out in a market that rewards speed over substance. Strategic AI is creating new competitive moats—not through features, but through faster learning cycles and message adaptation. AI leveled the playing field in how companies write, pitch, sell and even how they build. Code, content, and product delivery are now faster and more accessible than ever. That means the only real edge left is how quickly you can differentiate before someone else copies you. For companies watching their GTM costs soar while conversion rates stagnate, the solution isn't generic AI tools that speed up misfires. It's precision platforms that restore competitive advantage. The teams winning today aren't scaling volume. They're scaling insight. They know who to target, what to say, and when to move. They're not chasing trends; they're setting them. Clay and Octave function as go-to-market operating systems. Clay transforms guesswork into actionable signals. Octave converts noise into message discipline. Octave's CEO, Vidibor, elaborates, 'Used together, they don't just reduce costs; they rebuild competitive moats that actually matter.' Hundreds of companies have already deployed both Clay and Octave as a combined system, proving that in a world where every company sounds identical, clarity becomes currency. And adaptation speed determines survival. The next wave of growth isn't about more automation. It's about sharper targeting, clearer messaging, and real-time narrative control. That's what Clay and Octave are building.
