Specialized search for Machine Learning

10+ hour, 17+ min ago (919+ words) From corner offices in New York to conference rooms in Silicon Valley, business leaders are grappling with the same question: how will AI reshape our businesses? "At Amazon Web Services, we work backwards from the customer," said Julie Neenan Souza, Global Head of Sports at AWS, describing the company's famous approach of designing products around the ideal customer experience rather than building first and hoping customers follow. "I'm not interested in creating or suggesting anything that doesn't add value for the fan. It's always about identifying the problems the fan faces and finding ways to solve them." Sports consumption is changing rapidly, and the fast-growing world of technology is calling the plays. Using Amazon's working backward approach, it is clear that if fans want it, the leagues need to deliver the right moves. "It's all about fan choice. Historically, we…...

15+ hour, 22+ min ago (276+ words) A Consumer Reports investigation found prices differed by as much as 23% for the same item Senator Chuck Schumer (D-New York) is accusing Instacart of ripping off consumers by charging different prices for the same product to different customers. "This is jacking up grocery costs across New York City, Long Island, and across the nation," Schumer said Sunday. He claims the pricing tactics could cost certain families as much as $1,200 more per year. Schumer cited an investigation by Consumer Reports and Groundwork Collaborative, which found that some grocery prices differed by as much as 23% per item from one Instacart customer to the next. The magazine says Instacart's algorithmic pricing experiments were found to be happening through the platform at several of the nation's biggest grocery retailers,including Albertsons, Costco, Kroger, Safeway, Sprouts Farmers Market, and Target. According to Consumer Reports, "Instacart…...

1+ day, 7+ hour ago (773+ words) Machine learning failures usually start before modeling, with poor data understanding and preparation. Clean data, strong features, and correct metrics matter more than complex algorithms. Long-term ML success depends on testing, monitoring, and regular updates after deployment. Datasets usually hide missing values, duplicates or columns that are misleading at first glance. Without proper data understanding, the model learns wrong patterns and provides poor results. How to Avoid This: You should study the dataset before you begin modeling. Check basic statistics, value ranges and examples from each column. This step helps understand the project's scope. Also Read: Best GPUs for Machine Learning and AI Workloads Real-world data is usually unstructured. Text may appear in numeric fields, dates might be written in different styles and cells might contain null values. Ignoring these problems can lead to unstable performance. How to Avoid This:…...

2+ day, 9+ hour ago (332+ words) Online lies spread using Artificial Intelligence are causing havoc in conflict zones and resulting in deaths, the Freedom Association has warned. Fake reports of atrocities in countries including Sudan shatter trust and stop people making donations with dire consequences for those in genuine need of help, according to chairman David Campbell Bannerman. He wants AI misinformation treated as an "urgent international danger, warning of the threat to democracy. He said: "Democracies depend on shared facts, accountable institutions, and citizens who can tell truth from manipulation. If AI bots can impersonate real people, dictate narratives, and drown out authentic voices, public debate becomes impossible. Without honest debate, free societies cannot function. In the conflict in Sudan, he said: "AI has been weaponised to spread fabricated images, videos, and crisis reports. Deepfakes have portrayed atrocities that never happened and these have since…...

2+ day, 15+ hour ago (528+ words) Image courtesy by QUE.com Machine Learning (ML) is a subset of AI focused on developing algorithms that allow computers to learn from and make predictions based on data. It enables systems to improve their performance on a specific task over time without being explicitly programmed. Machine Learning is utilized in various applications, such as fraud detection, recommendation systems, and autonomous vehicles. Its capabilities extend to recognizing patterns in complex datasets, making it an invaluable tool for solving real-world problems. Deep Learning is a specialized and more advanced form of Machine Learning characterized by its use of neural networks. It mimics the human brain's structure and function, consisting of interconnected layers (hence "deep") that process input data and gradually extract higher-level features. Deep Learning thrives in environments with ample data and computing resources, powering breakthroughs in image and speech recognition, natural…...

3+ day, 18+ hour 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 ......

3+ day, 23+ hour 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....

4+ day, 1+ hour 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…...

4+ day, 4+ hour ago (627+ words) This study leverages advanced genomics and machine learning to refine the understanding of key fruit quality traits in peaches. Using whole-genome resequencing data from an F1 progeny of two distant peach cultivars, the researchers constructed an ultra-high-density genetic map, identifying key quantitative trait loci (QTLs) for traits such as fruit shape, color, and maturity. Notably, the study introduces machine learning models for more accurate phenotyping of fruit color, revealing two previously undetectable QTLs for peach flesh color variation. These innovations provide a new framework for precision breeding, enhancing peach quality and other complex traits through improved mapping and phenotyping strategies. Peach (Prunus persica) is an economically important fruit, and understanding the genetic basis of its quality traits is crucial for breeding. Recent advances in genome sequencing have led to the construction of detailed genetic maps, enabling deeper insights into the inheritance…...

4+ day, 6+ hour 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....