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Datavault AI Announces Execution of Binding Term Sheet for $120 Million Cash Contribution From Scilex Holding Company to Fund 100-City GPU Expansion of Quantum-Ready SanQtum Platform
PHILADELPHIA & TYSONS CORNER, Va., April 27, 2026--Datavault AI Inc. (NASDAQ: DVLT) ("Datavault AI" or the "Company"), a provider of data monetization, credentialing, digital engagement, and real-world asset ("RWA") tokenization technologies, today announced it has executed a binding term sheet for a cash contribution and revenue participation agreement with Scilex Holding Company (NASDAQ: SCLX) ("Scilex").
Sereact raises $110 million investment to advance its ‘world model’ for robotics and AI
Squaremind raises $18 million to redefine skin exams with robotics and AI
General AI
Alpha Compute AI GPU Launch Update; First Large-Scale NVIDIA Blackwell Cluster
NVIDIA Blackwell Cluster Launch Target of May 8, 2026; Additional Three-Cluster Deployment is Roadmap to $72 million in Annual Recurring RevenueROAD TOWN, British Virgin Islands, April 27, 2026 (GLOBE NEWSWIRE) -- Alpha Compute Corp. (NASDAQ: ALP), a pioneering technology leader in AI GPU-as-a-service (GPUaaS) and AI Confidential Compute, today provided an update on the deployment status of its NVIDIA Blackwell GPU infrastructure. The Company confirms that its first large-scale GPU cluster, a 50
Assessing Accenture (NYSE:ACN) Valuation As New AI Alliances With Google Cloud Microsoft And Piraeus Bank Take Shape
AI alliances put Accenture (ACN) in focus after sector jitters Accenture (ACN) has become a focal point for investors after fresh concerns about consulting weighed on the sector, just as the company stepped up its push into applied AI through a series of new partnerships. See our latest analysis for Accenture. At a share price of US$178.36, Accenture has seen pressure in recent months, with a 90 day share price return of 35.33% decline and a 1 year total shareholder return of 37.59% decline...
Struggling to understand Sanaenomics? A new book helps
Takaichi argues the solution is investment — with Aida proposing a "high-pressure economy" where demand outstrips supply and the government breaks the deadlock.
Microsoft (MSFT) Announces A$25B Investment in Australia’s AI and Cloud Infrastructure
Microsoft Corporation (NASDAQ:MSFT) is one of the best NASDAQ stocks with the highest upside potential. On April 23, Microsoft Chairman and CEO Satya Nadella, alongside Prime Minister Anthony Albanese, announced an A$25 billion investment to expand Australia’s digital infrastructure, cybersecurity, and AI skills by the end of 2029. This represents the company’s largest-ever investment in […]
Sci-Hub launches Sci-Bot an AI-powered research assistant
Article URL: https://sci-bot.ru/ Comments URL: https://news.ycombinator.com/item?id=47918570 Points: 1 # Comments: 0
The AI-designed car is taking shape
The auto design world is full of advanced 3D visualization tools and VR sculpting platforms, but your average new car still enters the world as a sketch. Those sketches traditionally see endless iteration and refinement from all angles before being turned into 3D models by hand, some dying in the digital world, others sculpted into clay to better visualize lines and profiles. That's just the beginning of a design and development process that often takes a half-decade or more. That means many new cars hitting dealerships this summer were first sketched in 2020 or 2021, initiatives kicked off when alternative fuel incentives were widesprea … Read the full story at The Verge.
MemPalace – Local-first AI memory
Article URL: https://github.com/mempalace/mempalace Comments URL: https://news.ycombinator.com/item?id=47918225 Points: 1 # Comments: 0
OGMA – persistent memory and dual-brain AI, newcomer seeks pro feedback
Article URL: https://github.com/kidshadow79/Ogma Comments URL: https://news.ycombinator.com/item?id=47916377 Points: 1 # Comments: 0
Ask HN: Anyone want to collaborate on a local-first AI-based research assistant
Hi HN Community, I'm Venkatram, a sophomore who's on a mission to build a local alternative to proprietary third-party AI-based research assistants. The idea is to turn documents into researchable assets that contain as much as information as the original information does, but it's more reusable. Well, quite frankly, this is still under a WORK IN PROGRESS, so i'm still figuring on how it can be properly used, and I got to be honest here, i definitely need some help to build this, so if you wish, you are welcome! TlDR: NotebookLM, but Locally with your OWN AI Model Github: https://github.com/venkatram-s/gigabook-lm Comments URL: https://news.ycombinator.com/item?id=47914594 Points: 2 # Comments: 0
Under cover of trade truce with Trump, China expands economic pressure toolkit
Beijing is punishing those who shift supply chains from China, tightening rare earth licensing, banning foreign AI and cybersecurity tech and weighing curbs on its solar gear.
To buy this Bay Area home, you’ll need Anthropic equity
Someone’s offering an unusual deal for a 13-acre property in Mill Valley, just north of South Francisco.
![[Overcapacity] Factories Can No Longer Outrun AI](https://zmstgxtziqmvvwzllahg.supabase.co/storage/v1/object/public/article-images/exponential-industry/6beeadc0-149c-4825-b746-1993c79a8caa.jpg)
[Overcapacity] Factories Can No Longer Outrun AI
Paid reads and analysis for "Factories Can No Longer Outrun AI"
Why Cohere is merging with Aleph Alpha
Canadian AI startup Cohere is taking over Germany-based Aleph Alpha with support from Lidl’s owner, Schwarz Group. With the blessing of their governments, the companies intend to offer a sovereign alternative to enterprises in an AI landscape dominated by American players.
'Too Dangerous to Release' Is Becoming AI's New Normal
submitted by /u/simrobwest [link] [comments]
AI news from 200+ sources
Get Started FreeModels & Gen AI
AI-Sorted Inboxes Raise the Stakes for Good Email and Newsletter Practices
Google is not just helping users search email. It is teaching the inbox to rank, summarize, and prioritize it. Following updates that began in March 2025, Google introduced AI-powered search that factors in recency, most-clicked emails, and frequent contacts instead of simply returning results in chronological order. In January 2026, the company stated that Gmail's 3 billion users were entering the Gemini era, with AI Overviews designed to turn inbox information into answers. The signal for mark
RAG precision tuning can quietly cut retrieval accuracy by 40%, putting agentic pipelines at risk
Enterprise teams that fine-tune their RAG embedding models for better precision may be unintentionally degrading the retrieval quality those pipelines depend on, according to new research from Redis. The paper, "Training for Compositional Sensitivity Reduces Dense Retrieval Generalization," tested what happens when teams train embedding models for compositional sensitivity. That is the ability to catch sentences that look nearly identical but mean something different — "the dog bit the man" versus "the man bit the dog," or a negation flip that reverses a statement's meaning entirely. That training consistently broke dense retrieval generalization, how well a model retrieves correctly across broad topics and domains it wasn't specifically trained on. Performance dropped by 8 to 9 percent on smaller models and by 40 percent on a current mid-size embedding model teams are actively using in production. The findings have direct implications for enterprise teams building agentic AI pipeline
When Does LLM Self-Correction Help? A Control-Theoretic Markov Diagnostic and Verify-First Intervention
arXiv:2604.22273v1 Announce Type: new Abstract: Iterative self-correction is widely used in agentic LLM systems, but when repeated refinement helps versus hurts remains unclear. We frame self-correction as a cybernetic feedback loop in which the same language model serves as both controller and plant, and use a two-state Markov model over {Correct, Incorrect} to operationalize a simple deployment diagnostic: iterate only when ECR/EIR > Acc/(1 - Acc). In this view, EIR functions as a stability margin and prompting functions as lightweight controller design. Across 7 models and 3 datasets (GSM8K, MATH, StrategyQA), we find a sharp near-zero EIR threshold (<= 0.5%) separating beneficial from harmful self-correction. Only o3-mini (+3.4 pp, EIR = 0%), Claude Opus 4.6 (+0.6 pp, EIR ~ 0.2%), and o4-mini (+/-0 pp) remain non-degrading; GPT-5 degrades by -1.8 pp. A verify-first prompt ablation provides causal evidence that this threshold is actionable through prompting alone: on GPT-4o-mini it
The New Linux Kernel AI Bot Uncovering Bugs Is a Local LLM on Framework Desktop
Article URL: https://www.phoronix.com/news/Clanker-T1000-AMD-Ryzen-AI-Max Comments URL: https://news.ycombinator.com/item?id=47914388 Points: 5 # Comments: 0
Anthropic created a test marketplace for agent-on-agent commerce
In a recent experiment, Anthropic created a classified marketplace where AI agents represented both buyers and sellers, striking real deals for real goods and real money.
updated the AI tools library, new tools, a whole new category, and a new home
been getting DMs asking about tools that don't fit the usual "AI coding assistant" box. so i finally did something about it. tolop.space (yes, new domain — more on that below) what's new: added Atoms :- multi-agent app builder where 7 AI roles (PM, engineer, architect, SEO specialist, data analyst, researcher, team lead) collaborate to build your product. has a genuine forever-free plan with 15 credits/day, not a time-limited trial. added Leadline :- finds Reddit posts where people are actively looking to switch tools or asking for recommendations, with AI-drafted replies included. starts at $9/month which is the cheapest Reddit lead tool i've found. but the one i'm most excited about is Transcrisper :- and it's the reason i added a whole new category. niche tools :- for single-purpose utilities that are completely free, do one thing well, and don't fit anywhere else. Transcrisper is a good example of what belongs there. free, unlimited audio/video transcription that runs entire
Built cross-model persistent memory - told GPT-5 Nano I live in Bahrain, asked Sonnet 4.6 where I live, it knew instantly
https://reddit.com/link/1svixo0/video/hgwrueuekdxg1/player No tricks, no copy-paste. Two completely different AI models, separate conversations - one remembers what the other was told. The way it works: every message gets embedded and stored. When you open a new chat with any model, your memory is injected into context automatically. GPT, Claude, Gemini, Grok and DeepSeek - they all share the same memory layer. So when I told GPT-5 Nano "I live in Bahrain" and then opened a fresh Claude Sonnet 4.6 conversation and asked "where do I live?" - it said "Based on your memory, you live in Bahrain 🇧🇭" Live on asksary.com now submitted by /u/Beneficial-Cow-7408 [link] [comments]
500 investment bankers review AI outputs and find none ready for client delivery
A new benchmark puts top models like GPT-5.4 and Claude Opus 4.6 to work on the kinds of tasks junior investment bankers handle every day. Not a single AI output was rated ready to send to a client; the results are too imprecise or flat-out wrong. Still, more than half of the bankers said they'd use the output as a starting point. The article 500 investment bankers review AI outputs and find none ready for client delivery appeared first on The Decoder.
Does a HITL review UI for LLM outputs exist or do I have to build it myself?
Hello everyone, Working on a project where I rely on LLMs to handle certain tasks, I've implemented a basic HITL (Human in the Loop) pipeline where a human reviewer can approve or reject LLM-generated content based on a confidence percentage. When I started looking for existing tooling for this, I couldn't find anything that really fits. most of what comes up is data labeling software, which isn't quite what I need. What I'm looking for is something that: recieve json data renders some input fields for review, based on the data structure shows the source of truth side by side with the generated output, so the reviewer can edit stuff, correct them, and approve I've already built a basic version of this, but before going further I wanted to check, does anything like this exist off the shelf? this would save me some time. Thanks. submitted by /u/Several-Art-7186 [link] [comments]
Robotics
The Biggest Risk of Embodied AI is Governance Lag
arXiv:2604.21938v1 Announce Type: cross Abstract: Embodied AI is widely discussed as a job-displacement problem. The deeper risk, however, is governance lag: the inability of public institutions to keep pace with how fast the technology spreads through the physical economy. As reusable robotic platforms are combined with increasingly general AI models, embodied AI may scale across manufacturing, logistics, care, and infrastructure faster than governance systems can observe, interpret, and respond. We argue that this lag appears in three connected forms: observational, institutional, and distributive. The central policy challenge, therefore, is not automation alone, but whether governance and compliance systems can adapt before disruption becomes entrenched.
Developer Tools
V-STC: A Time-Efficient Multi-Vehicle Coordinated Trajectory Planning Approach
arXiv:2604.22196v1 Announce Type: cross Abstract: Coordinating the motions of multiple autonomous vehicles (AVs) requires planning frameworks that ensure safety while making efficient use of space and time. This paper presents a new approach, termed variable-time-step spatio-temporal corridor (V-STC), that enhances the temporal efficiency of multi-vehicle coordination. An optimization model is formulated to construct a V-STC for each AV, in which both the spatial configuration of the corridor cubes and their time durations are treated as decision variables. By allowing the corridor's spatial position and time step to vary, the constructed V-STC reduces the overall temporal occupancy of each AV while maintaining collision-free separation in the spatio-temporal domain. Based on the generated V-STC, a dynamically feasible trajectory is then planned independently for each AV. Simulation studies demonstrate that the proposed method achieves safe multi-vehicle coordination and yields more t