AI News Archive: April 28, 2026 — Part 22
Sourced from 500+ daily AI sources, scored by relevance.
- AI fakes of accused US press gala gunman flood social media
AI fakes of accused US press gala gunman flood social media The Straits Times
- GitHub Copilot switches to token-based billing in June 2026
Starting June 1, 2026, GitHub will charge Copilot users based on actual usage instead of premium request counts. The article GitHub Copilot switches to token-based billing in June 2026 appeared first on The Decoder .
- IBM launches AI platform Bob to regulate SDLC costs
To regulate software delivery costs and SDLC governance, IBM is launching Bob, an AI platform built to anchor enterprise engineering. Accumulated technical debt, hybrid cloud structures, and rigid compliance requirements clash with the raw speed of coding assistants. Without boundaries, they generate unmanaged liabilities rather than functional progress. Dinesh Nirmal, SVP at IBM Software, explained: […] The post IBM launches AI platform Bob to regulate SDLC costs appeared first on AI News .
- IBM launches AI development partner Bob
IBM launches AI development partner Bob verdict.co.uk
- Nvidia Nemotron 3 Nano Omni Powers Enterprise AI Agents
The model expands the AI chip giant’s non-hardware offerings.
- Introducing NVIDIA Nemotron 3 Nano Omni: Long-Context Multimodal Intelligence for Documents, Audio and Video Agents
Introducing NVIDIA Nemotron 3 Nano Omni: Long-Context Multimodal Intelligence for Documents, Audio and Video Agents
- Together AI Brings NVIDIA Nemotron 3 Nano Omni to Developers on Day 0
NVIDIA Nemotron 3 Nano Omni is now on Together AI: a single open model that reasons across video, images, audio, and text, built for agentic workloads at scale.
- NVIDIA Nemotron 3 Nano Omni Powers Multimodal Agent Reasoning in a Single Efficient Open Model
Agentic systems often reason across screens, documents, audio, video, and text within a single perception‑to‑action loop. However, they still rely on...
- Nvidia is no longer just selling the shovels. Nemotron 3 Nano Omni is the company’s most aggressive move into AI models.
Nvidia released Nemotron 3 Nano Omni on Tuesday, an open-weight multimodal AI model that unifies vision, audio, and language understanding in a single architecture designed to power autonomous AI agents on edge devices. The model has 30 billion parameters but activates only three billion per forward pass through a mixture-of-experts design, a ratio that allows […] This story continues at The Next Web
- Nvidia introduces Nemotron 3 Nano Omni with vision and speech for powerful agentic AI use
Nvidia Corp. today launched a powerful reasoning artificial intelligence model that unifies text, vision and speech, capable of acting as the “brains” of faster, smarter agentic AI applications. Dubbed Nemotron 3 Nano Omni, and weighing in at about 30 billion parameters, the new state-of-the-art model uses mixture-of-experts architecture to deliver extremely low latency and provides high flexibility and control. Nvidia combined vision and audio […] The post Nvidia introduces Nemotron 3 Nano Omni with vision and speech for powerful agentic AI use appeared first on SiliconANGLE .
- Claude for Creative Work
Claude for Creative Work
- Anthropic releases 9 Claude connectors for creative tools, including Blender and Adobe
Anthropic is targeting creative professionals with its latest Claude AI update. The company has released nine new Claude connectors that work with creative tools like Blender and more. more…
- Workshop: Build Your Technical AI Security Strategy in 90 Minutes (Repeat)
Workshop: Build Your Technical AI Security Strategy in 90 Minutes (Repeat) Gartner
- Claude Gains Integrations With Adobe, Blender, SketchUp and Other Creative Apps
Anthropic today updated Claude with new connectors aimed at creative professionals, adding integrations for Ableton, Adobe, Affinity, Autodesk Fusion, Blender, Resolume Arena and Wire, SketchUp, and Splice. Connectors are tools that Claude can use to access other platforms and help with completing tasks. Anthropic says that Claude can open up new ways for creatives to work and take on larger-scale projects. Ableton - Allows users to ask questions about the official product documentation for Live and Push. Adobe - More than 50 tools across Creative Cloud apps like Photoshop, Premiere, and Express are available. Affinity - The Affinity connector lets users automate repetitive production tasks and generate custom features. Autodesk Fusion - Fusion subscribers can create and modify 3D models through conversations with Claude. Blender - The Blender connector adds a natural-language interface for the Python API. Users can analyze and debug Blender scenes, build custom scripts to batch-apply
- Claude can now plug directly into Photoshop, Blender, and Ableton
Anthropic is also giving the Blender Foundation a load of cash to help the software stay free and open-source.
- Unlocking human ambition to drive business growth with AI
The post Unlocking human ambition to drive business growth with AI appeared first on Source .
- In An AI World, High-Performance IT Is Mandatory For Business Success
Technology leaders are operating in an environment defined by constant and accelerating disruption. AI adoption, geopolitical volatility, mounting technical debt, and unrelenting cost pressure demand that IT steps up for their business partners. Simultaneously, the tolerance of IT and CIO failures is waning as quickly, forcing a vision and strategy that goes beyond incremental improvement […]
- What CIOs told Forrester about building an AI‑ready digital workplace
What CIOs told Forrester about building an AI‑ready digital workplace Atlassian
- Enterprise AI is missing the business core
Enterprise AI is missing the business core InfoWorld
- 5 mistakes tech leaders make when deploying enterprise AI
The modern CIO has perhaps the hardest iteration of the job: transforming enterprises that run on SAP, ServiceNow and even fax machines into “AI-native,” “AI-first” organizations. From choosing between hundreds of platform options, to receiving yearlong timelines to spin up a few chatbots, to employees who just keep feeding their team’s internal data to ChatGPT, dozens of CIOs feel stuck between a rock and a hard place. But the pressure to increase operational efficiency grows each day, with 90% of enterprises actively adopting AI agents , and 79% of enterprises expect full-scale adoption of agentic AI in the next 3 years . It can feel impossible to know what to avoid and where to look more closely, on the path to enterprise AI transformation, which is why I’ve curated the top missteps I’ve noticed from working with hundreds of enterprises over the past few years to implement AI solutions. They’re hard-won insights, and I hope they’ll be useful. 1. Starting with the wrong use cases Oft
- The biggest missed opportunities for CIOs in the AI era
Somewhere right now, a CIO is sitting in a Board meeting trying to explain why the six AI tools the company has deployed in the last two years haven’t produced the ROI the board was promised. There’s an LLM in marketing. A summarizer in legal. Some bots in sales and customer service. The tools are live. The spend was significant. So where is the impact? The Board wants answers, but here’s the tough truth: The tools work. They just don’t work together. The real missed opportunity isn’t a tool Most organizations today have AI tools deployed across multiple departments. Even so, according to Boston Consulting Group, 74% of companies still struggle to achieve and scale real value from their AI investments. Why? The technology isn’t the problem. The biggest missed opportunity for CIOs right now is AI orchestration. Your company can have every tool it needs, but if none of them talk to each other, you don’t have a strategy—you have an expensive collection of silos. Orchestration in action Wh
- 77% of enterprise leaders say AI skills are urgent—so why is training still an afterthought?
At some point in the last two years, every company on earth held a meeting about AI. There were slides. There was enthusiasm. Someone said "paradigm shift." And then, in most cases, employees were handed a Claude or ChatGPT subscription and left to work out the rest themselves. But lobbing prompts at generative AI doesn't automatically make someone an expert. Just like buying a cookbook doesn't automatically make someone a chef. It takes time and guidance to learn a new skill. And when it come
- Enterprises are not running out of AI ambition — they are running out of time to act on it
Enterprise AI transformation has a new home: the boardroom. Across financial services, CEOs are now demanding results, not more roadmaps. As Google Cloud Next 2026 packed Las Vegas with announcements — from the Gemini Enterprise Agent Platform to eighth-generation Tensor Processing Units — a clear theme emerged among systems integration partners: The era of tinkering is […] The post Enterprises are not running out of AI ambition — they are running out of time to act on it appeared first on SiliconANGLE .
- Why AI agents are triggering a rethink of enterprise identity
We understand many organisations are still in the early stages of AI maturity , focusing on governance and basic controls around new technologies. One of the biggest challenges in this journey is integrating automation and AI securely into existing enterprise systems. As AI-driven attack surfaces expand, identity becomes a foundational control for securing automation and, critically, for limiting blast radius when things go wrong. Mistakes will happen; the goal of modern identity design is to ensure the impact is contained and recoverable. The rapid rise of AI agents is pushing identity controls away from a “bouncer at the door” analogy and toward continuous, context‑aware evaluation, throughout your systems and processes. Traditionally, once a user or service authenticated and received a token, that token could be replayed freely until expiry, sometimes for hours or days, without the platform rechecking whether anything important had changed about the subject's standing. This model no
- Webinar Today: A Step-by-Step Approach to AI Governance
Join the webinar to explore a practical, multi-layered roadmap to transition from fragmented AI usage to a governed, scalable ecosystem. The post Webinar Today: A Step-by-Step Approach to AI Governance appeared first on SecurityWeek .
- AI for Deal Acceleration: Faster Sales Cycles
Discover how AI accelerates deals by automating workflows, unifying GTM teams, and scaling top sales strategies for faster closes.
- Ensuring the Safety and Security of AI Systems
Ensuring the Safety and Security of AI Systems Carnegie Mellon University's Software Engineering Institute
- Hassan Ashtiani: Building trustworthy AI through mathematical foundations
Hassan Ashtiani, Professor, McMaster University | Vector Institute Faculty Member You want to share your medical data to help advance research, but you don’t want others to access your private […] The post Hassan Ashtiani: Building trustworthy AI through mathematical foundations appeared first on Vector Institute for Artificial Intelligence .
- 35-50% of planned AI data centres are behind schedule
35-50% of planned AI data centres are behind schedule smithschool.ox.ac.uk
- Korean shipbuilders eye AI data centers for growth
Korean shipbuilders eye AI data centers for growth 매일경제
- Approaches to Fairer Multilingual NLP: Perspectives on Data Quality and Model Interpretability
A:Kushal Jayesh Tatariya; TT; Research results; RL:Machine Learning & Data Science;
- Evaluating Large Language Models' Abilities to Process and Understand Technical Policy Reports
The authors detail their development of a specialized benchmark for evaluating large language models' abilities to process and understand technical policy reports, thus addressing a gap in existing domain-specific evaluation.
- A comprehensive taxonomy for large language models
A comprehensive taxonomy for large language models EurekAlert!
- Trust by design: How much can you really trust your AI agent
As the UK pours millions into agentic AI, trust by design is the missing piece.
- From hype to discipline: Delivering AI ROI in 2026
By Purushothaman KG- Partner and Head of Technology Transformation and AI, KPMG in India Artificial intelligence (AI) has firmly established itself at the center of business strategy discussions worldwide, increasingly […] The post From hype to discipline: Delivering AI ROI in 2026 appeared first on Express Computer .
- Google Cloud Next AI Keynote: 5 Takeaways for IT Leaders
Thomas Kurian’s Google Cloud Next keynote framed Google’s agentic AI vision. Here are five key takeaways for IT leaders. The post Google Cloud Next AI Keynote: 5 Takeaways for IT Leaders appeared first on TechRepublic .
- Waymo is coming to the Rose City!
Waymo is coming to Portland, Oregon, to bring its fully autonomous ride-hailing service to the city.
- Waymo car blocked an ambulance. Now it’s skipping an Austin safety meeting
Waymo car blocked an ambulance. Now it’s skipping an Austin safety meeting statesman.com
- Google Gemini is finally taking over the dashboard for millions of GM drivers
GM upgrades in-car AI with Gemini, starting with 2022 models.
- Gemini replacing Google Assistant on Android Automotive for 4 million GM cars
Following Android Auto , Gemini is coming to GM cars with Android Automotive (officially known as Google built-in). more…
- Recursive forecasting: Eliciting long-term forecasts from myopic fitness-seekers
We’d like to use powerful AIs to answer questions that may take a long time to resolve. But if a model only cares about performing well in ways that are verifiable shortly after answering (e.g., a myopic fitness seeker ), it may be difficult to get useful work from it on questions that resolve much later. In this post, I’ll describe a proposal for eliciting good long-horizon forecasts from these models. Instead of asking a model to directly predict a far-future outcome, we can recursively: Ask it to predict what it will predict at the next time step, Use its prediction at the next time step to provide intermediate rewards, Finally reward using ground truth at the last step. This lets us replace a single distant forecast with a chain of short-horizon forecasts, each verifiable shortly after answering. I call this proposal recursive forecasting . It does have limitations: for example, it requires that developers maintain control over the reward signal at least until the final step, which
- On the political feasibility of stopping AI
A common thought pattern people seem to fall into when thinking about AI x-risk is approaching the problem as if the risk isn’t real, substantial, and imminent even if they think it is. When thinking this way, it becomes impossible to imagine the natural responses of people to the horror of what is happening with AI. This sort of thinking might lead one to view a policy like getting rid of advanced AI chips is “too extreme” even though it’s clearly worth it to avoid (e.g.) a 10% chance of human extinction in the next 10 years. It might lead one to favor regulating AI, even though Stopping AI is easier than Regulating it . It might lead one to favor safer approaches to building AI that compromise a lot on competitiveness, out of concern that society will demand a substitute for the AI that they don’t get to have. But in fact, I think there is likely a very narrow window between “society not being upset enough to do anything substantial to govern AI” and “society being so upset that gett
- ‘It is about choice — if you want to hear AI music or if you don't.’ One Spotify user got so frustrated with AI slop that they created an ‘AI blocker’, but it 'may violate Spotify's terms of service'
A Spotify user has built their own software that filters out AI-generated music from their listening experiences.
- Over 80% of US government agencies already use AI agents - and it's only the beginning
A new survey finds most government leaders believe that by 2030, the public sector will consist of humans and AI agents working together.
- Fragmented AI policy threatens US leadership as government scrambles to keep pace
AI policy fragmentation is emerging as a critical risk for Washington, and without a federal standard, a patchwork of conflicting state-level rules threatens to undermine American competitiveness. That gap is precisely what Appian Corp. is moving to address at the highest levels of government. The process automation company serves federal, state and local agencies — from the […] The post Fragmented AI policy threatens US leadership as government scrambles to keep pace appeared first on SiliconANGLE .
- Xiaomi releases MIT‑licensed MiMo models for long‑running AI agents
Xiaomi has released and open-sourced MiMo-V2.5 and MiMo-V2.5-Pro under the MIT License, giving developers another potentially lower-cost option for building AI agents that can run longer tasks such as coding and workflow automation. Both models support a 1-million-token context window, the company said. MiMo-V2.5-Pro is designed for complex agent and coding tasks, while MiMo-V2.5 is a native omnimodal model that supports text, images, video, and audio. The release comes as agentic AI workloads are putting new pressure on enterprise AI budgets. These systems can burn through large numbers of tokens as they plan, call tools, write code, and recover from errors, making cost and deployment control increasingly important for developers. By using the MIT License , Xiaomi said it is allowing commercial deployment, continued training, and fine-tuning without additional authorization. Tulika Sheel , senior vice president at Kadence International, said the MIT License can make it attractive. “It
- OpenAI’s Symphony spec pushes coding agents from prompts to orchestration
OpenAI’s Symphony spec pushes coding agents from prompts to orchestration InfoWorld
- Fleet hopes to be the MDM provider for the AI Era
Fleet, the independent, open-source, multi-platform MDM service, recently announced its new partner program for VARs and MSPs serving enterprise customers and recruited MobileIron co-founder Suresh Batchu to serve on the company’s board. With those moves in mind, I caught up with company CEO Mike McNeil to find out more about the Fleet’s plans. Given the company’s roots in open source, working with partners is a good way to enable it to support a variety of enterprise needs, with resellers and MSPs playing an active role in customizing the core solution for those requirements. Fleet and the Mac Fleet is just as happy managing Macs as it is Linux systems and integrates well with existing tools — as long as they support open standards and APIs. This gives it a unique insight into Apple device adoption in the enterprise. McNeil confirmed that both Apple and Linux systems are seeing rapid increases in deployment. “The new MacBook Neo is now cheaper than comparable PCs, so Apple adoption is
- South Africa used AI to write its AI policy. The citations were fake.
South Africa’s Department of Communications and Digital Technologies spent months drafting a national artificial intelligence policy. It proposed a National AI Commission, an AI Ethics Board, an AI Regulatory Authority, an AI Ombudsperson, a National AI Safety Institute, and an AI Insurance Superfund. It outlined five pillars of AI governance: skills capacity, responsible governance, ethical […] This story continues at The Next Web
- How will AI change operating systems? Part 1: Ubuntu and Linux
A deepdive with the Canonical team into how AI is changing Ubuntu, why they’re betting on local-first LLMs, and a look into other Linux distributions