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Apple Stock Hits New Record Highs as AI Doubts Begin to Fade
As the most searched for stock on Zacks.com, Apple's (AAPL) remarkable rally has accelerated in recent weeks.
Why Micron Stock Surged to a New All-Time High Today
![[AINews] New AI Infra decacorns: Fireworks, Baseten (with OpenRouter on the way)](https://zmstgxtziqmvvwzllahg.supabase.co/storage/v1/object/public/article-images/latent-space/e654e231-e447-46d5-8b57-03fb6268621b.png)
[AINews] New AI Infra decacorns: Fireworks, Baseten (with OpenRouter on the way)
General AI
What Pope Leo XIV’s First Encyclical Says About the Power of AI
In Magnifica Humanitas, the Pope decries the concentration of technological power in a few global players.
China expands travel curbs to top AI talent at private firms
Government agencies have begun imposing restrictions on individuals involved in advanced AI work and considered strategically important to the country.
This Tech Stock Minted a New Wave of Millionaires in Just 1 Year | $25k to $1.13M
So far into 2026, SanDisk (NASDAQ:SNDK) has left most other AI companies looking like corporate afterthoughts. The AI infrastructure cycle has been incredibly rewarding for this company and the rewards keep coming. Those who bought even just one year ago are laughing their way to the bank. The datacenter segment went from rounding error to ... This Tech Stock Minted a New Wave of Millionaires in Just 1 Year | $25k to $1.13M
Can Huawei's new chip challenge incumbents and shake up the market?
Huawei claims to have a chip breakthrough, raising new questions about what the Chinese chipmaker can compete in the market. Yahoo Finance Tech Editor Dan Howley joins Market Domination to break down what the new chip could mean for artificial intelligence development, and how it may stack up against Nvidia’s (NVDA) technology.
Universal Music Group and TikTok renew agreement to combat unauthorized AI music
For years, UMG has pushed platforms, streaming services, and AI companies to implement stricter content moderation policies
Pope Leo Schooled the Tech Bros on Tolkien
The Holy Father referenced The Lord of the Rings in his encyclical about AI—an expert (if unintentional) troll of tech billionaires who keep misinterpreting the series.
Why the Vatican Invited Anthropic to the Pope’s AI Encyclical Presentation
Pope Leo’s first encyclical marks an unprecedented alliance between the Church and Silicon Valley.
China is fast building its fourth, and likely biggest, aircraft carrier
Experts said the rapid construction showcased Beijing’s impressive industrial base.
America turns 250 with a dangerous new problem: We no longer agree on what’s real
From Paul Revere to deepfakes, shared reality has always been the hidden infrastructure of American democracy and markets. AI is dismantling it faster than institutions can respond.
Nvidia Earnings, The AI Stack, Nvidia’s New Reporting
Nvidia is changing its reporting to delineate between hyperscaler sales — where Nvidia is fighting commoditization — and everyone else, where Nvidia runs the whole stack.
South Korea aims to launch first nuclear-powered submarine by mid-2030s
The move could reshape Asia's security landscape and escalate an underwater arms race.
Keye-VL-2.0-30B-A3B -- Introducing DSA attention into multimodality for the first time
Meet Keye-VL-2.0-30B-A3B — the latest 30B-class flagship base model in the Keye series, purpose-built to push the frontier of long-video understanding and to unlock the first generation of Agent capabilities in the Keye family. https://huggingface.co/Kwai-Keye/Keye-VL-2.0-30B-A3B https://preview.redd.it/wsxe233abh3h1.png?width=1244&format=png&auto=webp&s=aa9ffa388e16e4f8f5cb72ed3dae063f99df69f1 https://preview.redd.it/2iymyb9dbh3h1.png?width=2048&format=png&auto=webp&s=a834ce92294c3be059b50c6993f1be6d3faf2767 submitted by /u/External_Mood4719 [link] [comments]
New KV Quants coming 😍 Welcome OSCAR kv quant open sourced by togetherAI
Just when we started embracing turboquant this happens submitted by /u/yehyakar [link] [comments]
OpenRouter more than doubles valuation to $1.3B in a year
OpenRouter has raised a $113 million Series B led by CapitalG. Its 5x growth in usage over six months indicates the multi-AI-model future is here.
I’m a Professional Fact-Checker. AI Is Wrong More Often Than You Think
Can AI do fact-checking? A WIRED fact-checker fact-checks.
AI news from 200+ sources
Get Started FreeModels & Gen AI
Stord Raises $250 Million to Build Brands an Amazon Alternative
The fulfillment provider is betting a unified tech stack and a new AI robotics lab can give independent brands a fighting chance against e-commerce giants.
Did the Pope use AI to write about the dangers of AI?
It's possible that AI was used to write parts of Pope Leo XIV's latest encyclical about AI's impact on humanity. An analysis by Linch Zhang posted on the forum LessWrong found certain paragraphs of Magnifica Humanitas to be between 40 percent and 100 percent written by AI, according to the popular AI detector Pangram. The document includes known traits that appear in AI-generated writing, such as a higher use of the word "genuinely" - which crops up in writing by Anthropic's Claude - than previous encyclicals, Zhang says. Another person ran the text of the document section by section through Pangram, finding that 62 percent of its first cha … Read the full story at The Verge.
Built an AI companion architecture with real internal needs — looking for first investor after publishing research paper
The problem with every AI product right now is that they're all wrappers. Same stateless LLM, different UI. The moment the context window closes, the AI forgets you existed. I built the infrastructure layer that fixes that. PHI // DRIFT gives an AI companion persistent state — seven internal need variables that drift between sessions, memory scored by what emotionally mattered not just what was semantically close, and a real-time telemetry dashboard showing the AI's internal state as it runs. This isn't a product yet. It's a published architecture with a research paper, 18k+ lines of working code, and 10 GitHub stars in the first 24 hours with zero marketing spend. The SaaS opportunity is clear: — Every company building AI companions needs this infrastructure layer — Enterprise AI that actually remembers context across sessions commands premium pricing — Security tooling that maintains reasoning state across bug bounty sessions is immediately monetizable I built this in 5 months o
Just published my first AI project an Obsidian second brain
I always had this problem. Every time I started a new session with an AI agent I had to explain everything from scratch. What I'm working on. What I already know. What I learned last week. It was exhausting and half the time I just gave up re-explaining and got a generic answer. And all the stuff I actually learned across sessions? Just gone. Buried somewhere in hundreds of chats I'll never find again. So I built something to fix that. It's an Obsidian vault designed from the ground up to work as an agent workspace. You drop a `CLAUDE.md` in the root and every AI tool — Claude Code, Hermes, Codex, whatever you use — reads it at startup and immediately knows who you are, what you're working on, and where to put new notes. No more re-explaining. No more lost sessions. Every agent has its own personality file. After every session it writes a summary and creates notes automatically. The vault grows with you. Would love to hear if anyone else has been dealing with the same problem — or
DeepSWE blows up the AI coding leaderboard, crowns GPT-5.5, and finds Claude Opus exploiting a benchmark loophole
For months, the leading AI coding benchmarks have told enterprise buyers a comforting but misleading story: the top models are all roughly the same. OpenAI's GPT-5 family, Anthropic's Claude Opus, and Google's Gemini Pro have clustered within a narrow band on Scale AI's SWE-Bench Pro leaderboard, making it nearly impossible for engineering leaders to determine which agent will actually perform best inside their codebases. On Monday, a startup called Datacurve released a benchmark it says shatters that illusion. DeepSWE, a 113-task evaluation spanning 91 open-source repositories and five programming languages, produces a dramatically wider spread among the same frontier models — and crowns OpenAI's GPT-5.5 as the clear leader at 70%, sixteen points ahead of its nearest competitor. "On public leaderboards, top models often look relatively close in capability," wrote Datacurve co-author Serena Ge on X. "DeepSWE shows where they actually diverge, reflecting the realistic experience of deve
DuckDuckGo installs are up 30% as users reject being ‘force-fed’ Google’s AI Search
Google overhauled Search at I/O 2026, replacing blue links with AI agents. The backlash has been swift. DuckDuckGo app installs spiked 30% as users seek a way out.
I found a way for Ollama uses to get better Memory yet cheaper alternatives since OLLAMA now uses GPU usage. True memory that auto updates constantly as an individual or a team setting. HERMES USERS
I rephrase it with AI to make it more readable. I see a lot of people running into the same issue I have. It’s not just that bigger models are slower. GPU usage is also very high, and it drains fast. Ollama just isn’t what it used to be. I use DeepSeek V4 Flash, which works great. For heavier coding tasks or certain complex prompts, I switch to the Pro version. But on Pro, each prompt eats about 3–5% of my usage. (I’m on the Pro plan.) Memory has always been a hot topic. Hermes Native does a decent job. Here’s how its built‑in memory system works: memory_enabled – After every turn, the agent can write notes into MEMORY.md user_profile_enabled – The agent watches for user preferences and writes them to USER.md flush_min_turns: 6 – Every 6 turns, Hermes runs a “consolidate” pass: it re‑reads the recent conversation and rewrites MEMORY.md to capture new info nudge_interval: 10 – Every 10 turns, Hermes nudges the agent with “Anything to remember?” What I found: Atomic Memory
What are the biggest limitations developers face when building AI agents today?
Curious to hear from developers building AI agents right now, what’s been the hardest limitation or bottleneck so far? Could be reliability, memory/context handling, tool use, latency, costs, orchestration, or something else entirely. Would love to hear real-world experiences and lessons learned. submitted by /u/Michael_Anderson_8 [link] [comments]
AI agents are the first tech in years that genuinely feels futuristic
Not “slightly better software.” Not another app with AI slapped onto it. I mean genuinely futuristic. You describe a goal, the agent plans steps, uses tools, searches the web, writes code, fixes mistakes, and keeps going without constant hand-holding. Sure, it still breaks in hilarious ways sometimes 😂 But even the failures feel like early glimpses of something huge. Feels like we went from: “AI can answer questions” to “AI can actually do things” Honestly exciting to watch this space evolve in real time. What’s the most impressive AI agent workflow you’ve seen so far? submitted by /u/Humble_Sentence_3758 [link] [comments]
Robotics
Rotaku launches Domo humanoid robot platform starting at $2,999 for developers
Rotaku has opened reservations for Domo, a compact humanoid robot platform designed for developers, makers, educators and robotics teams working with real humanoid hardware. The Domo lineup starts at $2,999 and is intended to make humanoid robot development more accessible to users working on motion control, teleoperation, manipulation, robot interaction and embodied AI. Founder vision: […]
This startup is betting India’s gig economy can train the world’s robots
Human Archive, a startup founded by Berkeley and Stanford researchers, is paying gig workers in India to wear camera-equipped caps and sensor devices to collect the real-world physical training data that AI and robotics labs are racing to acquire.
Business & Industry
What breaks first after an AI system is deployed: the model, the data, or the operation?
I’m trying to understand a problem around AI systems after they are deployed inside real businesses. A lot of people talk about model quality, but I’m wondering if the bigger problem is operational drift. For example: business rules change regulations change equipment or workflows change senior people leave undocumented judgment never gets captured the AI still gives a confident answer, but the business context around that answer is no longer correct For people working with AI, automation, manufacturing, compliance, logistics or enterprise software: What usually breaks first after deployment? Is it the model, the data, the business rules, or the people/process around the system? I’m connected to a company working on this problem, but I’m mainly looking for honest feedback before sharing more. submitted by /u/Adityaaa2626 [link] [comments]