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Your best data science team just spent six months building a model that predicts customer churn with 90% accuracy. It’s sitting on a server, unused. Why? Because it’s been stuck in a risk review queue for a very long period of time, waiting for a committee that doesn’t understand stochastic models to sign off. This isn’t a hypothetical — it’s the daily reality in most large companies.
In AI, the models move at internet speed. Enterprises don’t.
Every few weeks, a new model family drops, open-source toolch
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The Supreme Court will decide whether Trump's tariffs under the IEEPA were legal, a ruling that could expand or limit presidential trade authority. Read more ›
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VentureBeat
When researchers at Anthropic injected the concept of "betrayal" into their Claude AI model's neural networks and asked if it noticed anything unusual, the system paused before responding: "Yes, I detect an injected thought about betrayal."The exchange, detailed in new research published Wednesday, marks what scientists say is the first rigorous evidence that large language models possess a limited but genuine ability to observe and report on their own internal... Read more ›
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Some enterprises are best served by fine-tuning large models to their needs, but a number of companies plan to build their own models, a project that would require access to GPUs. Google Cloud wants to play a bigger role in enterprises’ model-making journey with its new service, Vertex AI Training. The service gives enterprises looking to train their own models access to a managed Slurm environment, data science tooling and... Read more ›
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Enterprise AI agents today face a fundamental timing problem: They can't easily act on critical business events because they aren't always aware of them in real-time.The challenge is infrastructure. Most enterprise data lives in databases fed by extract-transform-load (ETL) jobs that run hourly or daily — ultimately too slow for agents that must respond in real time.One potential way to tackle that challenge is to have agents directly interface with... Read more ›
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Watch out, DeepSeek and Qwen! There's a new king of open source large language models (LLMs), especially when it comes to something enterprises are increasingly valuing: agentic tool use — that is, the ability to go off and use other software capabilities like web search or bespoke applications — without much human guidance. That model is none other than MiniMax-M2, the latest LLM from the Chinese startup of the same... Read more ›
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OpenAI has introduced Aardvark, a GPT-5-powered autonomous security researcher agent now available in private beta.Designed to emulate how human experts identify and resolve software vulnerabilities, Aardvark offers a multi-stage, LLM-driven approach for continuous, 24/7/365 code analysis, exploit validation, and patch generation!Positioned as a scalable defense tool for modern software development environments, Aardvark is being tested across internal and external codebases. OpenAI reports high recall and. Read more ›
21
Anthropic is making its most aggressive push yet into the trillion-dollar financial services industry, unveiling a suite of tools that embed its Claude AI assistant directly into Microsoft Excel and connect it to real-time market data from some of the world's most influential financial information providers.The San Francisco-based AI startup announced Monday it is releasing Claude for Excel, allowing financial analysts to interact with the AI system directly within their... Read more ›
15
In an industry where model size is often seen as a proxy for intelligence, IBM is charting a different course — one that values efficiency over enormity, and accessibility over abstraction.The 114-year-old tech giant's four new Granite 4.0 Nano models, released today, range from just 350 million to 1.5 billion parameters, a fraction of the size of their server-bound cousins from the likes of OpenAI, Anthropic, and Google. These models... Read more ›
14
Presented by Axis Communications Many businesses are equipped with a network of intelligent eyes that span operations. These IP cameras and intelligent edge devices were once solely focused on ensuring the safety of employees, customers, and inventory. These technologies have long proved to be essential tools for businesses, and while this sentiment still rings true, they’re now emerging as powerful resources.These cameras and edge devices have rapidly evolved into real-time... Read more ›
12
Data security company Fortanix Inc. announced a new joint solution with NVIDIA: a turnkey platform that allows organizations to deploy agentic AI within their own data centers or sovereign environments, backed by NVIDIA’s "confidential computing" GPUs.“Our goal is to make AI trustworthy by securing every layer—from the chip to the model to the data," said Fortanix CEO and co-founder Anand Kashyap, in a recent video call interview with VentureBeat. "Confidential... Read more ›
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Recently, there has been a lot of hullabaloo about the idea that large reasoning models (LRM) are unable to think. This is mostly due to a research article published by Apple, "The Illusion of Thinking" Apple argues that LRMs must not be able to think; instead, they just perform pattern-matching. The evidence they provided is that LRMs with chain-of-thought (CoT) reasoning are unable to carry on the calculation using a... Read more ›
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Business Insider
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41% 19 |
Tom's Hardware
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Mashable
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6% 3 |
Wired
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5% 7 |
Eurogamer.net
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4% 3 |
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02.11.2025 06:56
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