Specialized search for Machine Learning

10+ hour, 33+ min ago (34+ words) Nine American companies have achieved a valuation of $1 trillion or more, and one of them is Tesla. Tesla is on track for a second straight year of declining electric vehicle sales, placing its ......

15+ hour, 54+ min ago (40+ words) Tennessee's first-of-its-kind artificial intelligence law could be in jeopardy. Noem was questioned about her department's deportation practices during a tense hearing in Washington, D.C. Tennessee's first-of-its-kind artificial intelligence law could be in jeopardy....

17+ hour, 31+ min ago (684+ words) Unveiling what it describes as the most capable model series yet for professional knowledge work, OpenAI launched GPT-5.2 today. The model was trained and deployed on NVIDIA infrastructure, including NVIDIA Hopper and GB200 NVL72 systems. It's the latest example of how leading AI builders train and deploy at scale on NVIDIA's full-stack AI infrastructure. AI models are getting more capable thanks to three scaling laws: pretraining, post-training and test-time scaling. Reasoning models, which apply compute during inference to tackle complex queries, using multiple networks working together, are now everywhere. But pretraining and post-training remain the bedrock of intelligence. They're core to making reasoning models smarter and more useful. And getting there takes scale. Training frontier models from scratch isn't a small job. It takes tens of thousands, even hundreds of thousands, of GPUs working together effectively. That level of scale demands excellence…...

23+ hour, 8+ min ago (33+ words) Modifying a deep neural network architecture to resemble natural brains resulted in an AI system that worked more efficiently with less training than standard models, according to a paper from Johns Hopkins University....

23+ hour, 45+ min ago (345+ words) In my Artificial Intelligence (AI) explainer, I have mentioned that AI is a broad concept and its aim is to create machines or computer systems that can perform tasks that require human intelligence. The term "artificial intelligence" was coined in 1956 at Dartmouth College, where researchers gathered and explored whether machines could simulate human cognitive ability. To enable computer systems to mimic human behavior, AI systems can use one of the many techniques: pre-programmed rules, learning from data, predefined algorithms, decision trees, and more. There is no bar on how you achieve Artificial Intelligence. Machine Learning (ML), on the other hand, is a subset of Artificial Intelligence. It's one of the techniques that allow machines to learn patterns from data rather than being explicitly programmed with rules. Basically, while AI is a broad concept, ML is a specific approach that enables AI…...

1+ day, 3+ hour ago (111+ words) ROCHESTER, N.Y. " A new Pew Research survey released on Tuesday says that 28% of teens use artificial intelligence daily. This comes after Pew Research conducted the survey from Sept. 25 to Oct. 9, having asked 1,458 teens online, ages 13 to 17. According to Pew, 64% of teens say they use AI chatbots like ChatGPT or Google Gemini. About 4% of teen respondents said they use AI chatbots "almost constantly," with 12% saying they use them several times daily, according to the study. AI Chatbot usage, according to survey respondents: Opposite to this, Pew found that 36% said they don't use AI chatbots. More of our AI coverage:...

1+ day, 12+ hour ago (35+ words) As 2025 begins to wind down, it will go down as another strong year for artificial intelligence (AI) stocks. Meanwhile, with AI still appearing to be in its early innings, the group could help lead ......

2+ day, 12+ min ago (730+ words) The debate over AI is often framed as a race toward ever greater capability. Faster chips. Bigger models. More capital. But capability is not the same as sustainability. The next phase of the AI cycle will be defined not only by breakthroughs but by AI limits. These limits are arriving on three fronts at once: economic, physical and moral. Each is already reshaping what comes next. For the past two years, AI has been fueled by a near boundless flow of capital. Trillions in market value have been added on expectations of future demand. Yet the economic AI limits are now becoming visible. That same tension is rising again. Revenue growth is real, but it remains highly concentrated in a small number of firms. Margins are under pressure as costs rise faster than pricing power. The result is a familiar…...

2+ day, 12+ hour ago (128+ words) Artificial intelligence was the hot topic in 2025. But not everyone is convinced it has changed the world. After all the hype and big spending, there has been a growing sense of unease that some of ... Technology: The State of artificial intelligence Artificial intelligence was the hot topic in 2025. But not everyone is convinced it has changed the world. Will AI start living up to the hype in 2026? After all the hype and big spending, there has been a growing sense of unease that some of the promises aren't being matched by reality. Office towers v Bunnings sheds: Alternate routes in AI race Demand for data centres to power the artificial intelligence boom is surging, but there is debate over the best way to deliver....

3+ day, 2+ hour ago (181+ words) Indian banks are rapidly adopting machine learning for Financial Crime Compliance as traditional rule'based systems lose effectiveness, a KPMG report says. - Indian Banks Accelerating AI Adoption for Financial Crime Compliance: Report Updated 9 December 2025 at 15:56 IST Indian banks are rapidly adopting machine learning for Financial Crime Compliance as traditional rule'based systems lose effectiveness, a KPMG report says. With RBI and SEBI pushing for responsible AI, institutions are moving to full'scale ML integration for AML, fraud detection and risk assessment, supported by tools like MuleHunter.AI. The Indian banks are rapidly integrating machine learning models into Financial Crime Compliance (FCC) operations amid rising fraud and regulatory scrutiny, making the traditional rule-based systems inadequate, KPMG said in a report. This is prompting financial institutions to shift to AI-driven frameworks for Anti-Money Laundering (AML), fraud detection and customer risk assessment, it said. Notably, the…...