Tag: Business

Presented by ArmA simpler software stack is the key to portable, scalable AI across cloud and edge. AI is now powering real-world applications, yet fragmented software stacks are holding it back. Developers routinely rebuild the same models for different hardware targets, losing time to glue code instead of shipping features. The good news is that a shift is underway. Unified toolchains and optimized libraries are making it possible to deploy models across platforms without compromising performance.Yet one critical hurdle remains: software complexity. Disparate tools, hardware-specific optimizations, and layered tech stacks continue to bottleneck progress. To unlock the next wave of AI innovation, the industry must pivot decisively away from siloed development and toward streamlined, end-to-end platforms.This transformation is already taking shape. Major cloud providers, edge platform vendors, and open-source communities are converging

Chinese e-commerce giant Alibaba’s famously prolific Qwen Team of AI model researchers and engineers has introduced a major expansion to its Qwen Deep Research tool, which is available as an optional modality the user can activate on the web-based Qwen Chat (a competitor to ChatGPT).The update lets users generate not only comprehensive research reports with well-organized citations, but also interactive web pages and multi-speaker podcasts — all within 1-2 clicks.This functionality is part of a proprietary release, distinct from many of Qwen’s previous open-source model offerings. While the feature relies on the open-source models Qwen3-Coder, Qwen-Image, and Qwen3-TTS to power its core capabilities, the end-to-end experience — including research execution, web deployment

DeepSeek, the Chinese artificial intelligence research company that has repeatedly challenged assumptions about AI development costs, has released a new model that fundamentally reimagines how large language models process information—and the implications extend far beyond its modest branding as an optical character recognition tool.The company's DeepSeek-OCR model, released Monday with full open-source code and weights, achieves what researchers describe as a paradigm inversion: compressing text th

Google AI Studio has gotten a big vibe coding upgrade with a new interface, buttons, suggestions and community features that allow anyone with an idea for an app — even complete novices, laypeople, or non-developers like yours truly — to bring it into existence and deploy it live, on the web, for anyone to use, within minutes.The updated Build tab is available now at ai.studio/build, and it’s free to start. Users can experiment with building applications without needing to enter payment information upfront, though certain advanced features like Veo 3.1 and Cloud Run deployment require a paid API key.The new features appear to me to make Google's AI models and offerings even more competitive, perhaps preferred, for many general users to dedicated AI startup rivals like Anthropic's Claude Code and OpenAI's Codex, respectively, two "vibe coding" focused products that are beloved by developer

Researchers at Mila have proposed a new technique that makes large language models (LLMs) vastly more efficient when performing complex reasoning. Called Markovian Thinking, the approach allows LLMs to engage in lengthy reasoning without incurring the prohibitive computational costs that currently limit such tasks.The team’s implementation, an environment named Delethink, structures the reasoning chain into fixed-size chunks, breaking the scaling problem that plagues very long LLM responses. Initial estimates show that for a 1.5B parameter model, this method can cut the costs of training by more than two-thirds compared to standard approaches.The quadratic curse of long-chain reasoningFor an LLM to solve a complex problem, it often needs to generate a long series of intermediate “thinking” tokens, often referred to as chain-of-thought (CoT). In recent years, researchers have found that using

Presented by Apptio, an IBM companyWhen a technology with revolutionary potential comes on the scene, it’s easy for companies to let enthusiasm outpace fiscal discipline. Bean counting can seem short-sighted in the face of exciting opportunities for business transformation and competitive dominance. But money is always an object. And when the tech is AI, those beans can add up fast.AI’s value is becoming evident in areas like operational efficiency, worker productivity, and customer satisfaction. However, this comes at a cost. The key to long-term success is understanding the relationship between the two — so you can ensure that the potential of AI translates into real, positive impact for your business. The AI acceleration paradoxWhile AI is helping to transform business operations, its own financial footprint often remains obscure. If you can’t connect costs to impact, how can you be sure your AI investments will drive mean

OpenAI is entering the browser world with the launch of ChatGPT Atlas, an AI-enabled browser. Atlas, now available globally, can be accessed through Apple’s macOS, with support for Windows, iOS and Android coming soon. The announcement comes several months after rumors in July that OpenAI would release a web browser that would challenge the dominance of Google’s Chrome. In a livestream, CEO Sam Altman said he hopes Atlas will help bring about a new way of interacting with and using the web, one where people chat with the browser rather than typing a URL. “We think AI represents a rare once-in-a-decade opportunity to rethink what a browser can be about and how to use one, and how to most productively and pleasantly use the web,” Altman said. “Tabs were great, but we haven’t seen a lot of innovation s

Presented by HPCreativity is quickly becoming the new measure of productivity. While AI is often framed as a tool for efficiency and automation, new research from MIT Sloan School of Management shows that generative AI enhances human creativity — when employees have the right tools and skills to use it effectively. That’s where AI PCs come in. These next-generation laptops combine local AI processing with powerful Neural Processing Units (NPUs), delivering the speed and security that knowledge workers expect while also unlocking new creative possibilities. By handling AI tasks directly on the device, AI PCs minimize latency, protect sensitive data, and lower energy consumption.Teams are already proving the impact. Marketing teams are using AI PCs to generate campaign assets in hours ins

Vibe coding is evolving and with it are the leading AI-powered coding services and tools, including Anthropic’s Claude Code. As of today, the service will be available via the web and, in preview, on the Claude iOS app, giving developers access to additional asynchronous capabilities. Previously, it was available through the terminal on developers' PCs with support for Git, Docker, Kubernetes, npm, pip, AWS CLI, etc., and as an extension for Microsoft's open source VS Code editor and other JetBrains-powered integrated development environments (IDEs) via Claude Agent. “Claude Code on the web lets you kick off cod

Hoping to attract more enterprise teams to its ecosystem, Adobe launched a new model customization service called Adobe AI Foundry, which would create bespoke versions of its flagship AI model, Firefly.Adobe AI Foundry will work with enterprise customers to rearchitect and retrain Firefly models specific to the client. AI Foundry version models are different from custom Firefly models in that Foundry models understand multiple concepts compared to custom models with only a single concept. These models will also be multimodal, offering a wider use case than custom Firefly models, which can only ingest and respond with images. Adobe AI Foundry models, with Firefly at its base, will know a compa