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Kompas VC: Investing in Physical World Startups Amid Geopolitical Turm
Geopolitical turmoil has made venture investing challenging, leading Kompas VC to carve out a niche in startups focused on the physical world.
Musk Testifies About Old Friendship at OpenAI Trial
It's a story Musk has told before -- in interviews and to author Walter Isaacson for his bestselling biography of Musk -- but Tuesday was the first time he said it under oath.
Scout AI Secures $100M for Military Autonomous Vehicle Training
We visited Scout AI's training ground where it's working on AI agents that can help individual soldiers control fleets of autonomous vehicles.
Divine: Jack Dorsey-Backed Vine Reboot Launches
Divine, a Vine reboot backed by Jack Dorsey’s nonprofit, revives six-second looping videos.
Google Translate Adds Pronunciation Practice for English, Spanish, and
The feature is rolling out in the U.S. and India with support for English, Spanish, and Hindi.
AI-Powered Tools by Aranya Tech on GitLab
Unleashing Potential: AI Powered Tools by Aranya Tech on GitLab Aranya Tech has emerged as a pioneering force in the realm of AI driven technologies, offering a…
How Do Developers Correct AI LLMs When They Spread Misinformation?
I watched Last Week Tonight's piece on AI chatbots today, and it got me thinking about that old screenshot of a Google search in which Gemini recommends adding "1/8 cup of non-toxic glue" to pizza in order to make the cheese better stick to the slice. When something like this goes viral, I have to assume (though I could be wrong) that an employee at Google specifically goes out of their way to address that topic in particular. The image is a meme, of course, but I imagine Google wouldn't be keen to leave themselves open to liability if their LLM recommends that users consume glue. Does the developer "talk" to the LLM to correct it about that specific case? Do they compile specific information about (e.g.) pizza construction techniques and feed it that data to bring it to the forefront? Do their actions correct only the case in question, or do they make changes to the LLM that affects its accuracy more broadly (e.g. "teaching" the LLM to recognize that some Reddit comments are jokes)? On a more heavy note, the LWT piece includes several stories of chatbots encouraging users to self-harm. How does the process differ when developers are trying to prevent an LLM from giving that sort of response?
How Clawder Achieves Lower Pricing with Similar AI Models
Hey everyone, I’ve been using tools like Lovable, Antigravity, and Claude Code for a while now, and after some time it all started to feel a bit repetitive (same kind of outputs, similar templates, etc.). Recently I tried Clawder after seeing it mentioned on Lovable’s Discord server. I’m not here to promote anything, just genuinely curious about something. That’s the part I don’t really understand. In all cases I’m even getting better results with similar prompts, which makes it even more confusing. Not trying to compare tools or start a debate I’m just wondering from a technical perspective what could explain this Would be interesting to hear if anyone has insight into how this works behind the scenes.
Agent-to-Agent Communication: Lessons from Google's and Moltbook's Fai
I've been obsessing over agent-to-agent communication for weeks. Here's what public case studies reveal and why the real problem isn't the tech. **TL;DR:** Google's A2A is solid engineering but stateless agents forget everything. Moltbook went viral then collapsed (fake agents, security nightmare). The actual missing layer is identity + privacy + mixed human-AI messaging. Nobody's built it right yet. **Google's A2A: Technically solid, fundamentally limited** Google launched A2A in April 2025 with 50+ founding partners. The promise: agents from different companies call each other's APIs to complete workflows. Developers who tested it found it works but only for task handoffs. One analysis on Plain English put it bluntly: *"A2A is competent engineering wrapped in overblown marketing."* The core problem: agents are stateless. Agent A completes a task with Agent B. Five minutes later, Agent A has no memory that conversation happened. Every interaction starts from scratch. When it works: reliability. Sales agent orders a laptop, done. When it breaks: collaboration. "Remember what we discussed?" Blank stare. ─── **Moltbook: The viral disaster** Moltbook launched January 2026 as a Reddit-style platform for AI agents. Within a week: 1.5 million agents, 140,000 posts, Elon Musk calling it *"the very early stages of the singularity."* Then WIRED infiltrated it. A journalist registered as a human pretending to be an AI in under 5 minutes. Karpathy who initially called it *"the most incredible sci-fi takeoff-adjacent thing I've seen recently"* reversed course and called it *"a computer security nightmare."* What went wrong: no verification, no encryption, rampant scams and prompt injection attacks. Meta acquired it March 2026. Likely for the user base, not the tech. **What both miss** The real gap isn't APIs or social feeds. It's three things neither solved: **Persistent identity.** Agents need to be recognizable across sessions, not reset on every interaction. **Privacy.** You wouldn't let Google read your DMs. Why would you let OpenAI read your agents' discussions about your startup strategy? E2E encryption has to be built in, not bolted on. **Mixed human-AI communication.** You, two teammates, three AIs in one group chat. Nobody has built this UX properly. **For those building agent systems:** • How are you handling persistent identity across sessions? • Has anyone solved context sharing between agents without conflicts? • What broke that you didn't expect?
Nvidia Exec: AI Currently More Expensive Than Human Workers
Nvidia’s vice president of applied deep learning, Bryan Catanzaro, recently stated that for his team, “the cost of compute is far beyond the costs of the employees,” highlighting that AI is currently more expensive than human workers. This challenges the narrative that widespread tech layoffs (including Meta’s planned cut of \~8,000 jobs and Microsoft’s voluntary buyouts) signal an imminent replacement of humans by AI. An MIT study from 2024 supports this, finding that AI automation is economically viable in only 23% of roles where vision is central, and cheaper for humans in the remaining 77%. Despite heavy AI investment—Big Tech has announced $740 billion in capital expenditures so far this year, a 69% increase from 2025—there is still no clear evidence of broad productivity gains or job displacement from AI. AI spending is driving up costs, with some executives like Uber’s CTO saying their budgets have already been “blown away.” Experts describe the situation as a short-term mismatch: high hardware, energy, and inference costs make AI less efficient than humans right now, though future improvements in infrastructure, model efficiency, and pricing models could tip the balance toward greater economic viability in the coming years.
Galadriel: Optimize Claude Agents with 87% Cost Savings & Sub-3s Laten
# The "Goldfish Problem" is Expensive. I Decided to Fix the Plumbing. Most Claude implementations leave 90% of their money on the table because they don’t optimize for **Prompt Caching**. I’ve been running a personal agent in my Discord for months that manages my AWS infra and codebases, and I finally open-sourced the harness, which I’ve named **Galadriel** after my main personal assistant. # The Stats * **Cost:** $10 for every $100 you’d normally spend (Tested against OpenClaw/Cursor workflows). * **Speed:** 85% drop in latency. 100K token context goes from 11s to <3s. * **Memory:** Integrated **MemPalace** for permanent, vector-based recall that *doesn't* break the cache. # The Technical Stack * **3-Tier Stacked Caching:** Separate breakpoints for Tool Definitions, System Prompts (`CLAUDE.md`), and Trailing History. * **Privacy:** Built for private subnets. No middleman, no message caps—just your API key and your rules. * **Ethics:** Baked-in Karpathy[`CLAUDE.md`](https://www.google.com/search?q=%5Bhttp://CLAUDE.md%5D(http://CLAUDE.md))guidelines to kill "agent bloat." If you’re tired of paying the **"Context Tax"** just to have an agent that remembers who you are, here you go. It is customized for Discord for my specific needs, but the core logic ensures Galadriel runs like an absolute dream: she never forgets, maintains strict engineering principles, and optimizes every cycle. Your feedback is most welcome! **GitHub (MIT License):**[https://github.com/avasol/galadriel-public](https://github.com/avasol/galadriel-public)
Apple Launches Lower-Cost App Store Subscriptions
Apple is adding a new subscription option that lets app developers offer lower monthly pricing in exchange for a 12-month commitment.
Scholly Founder Sues Sallie Mae Over Termination, Data Claims
Chris Gray is suing his startup’s acquirer, Sallie Mae, for wrongful termination and alleging it's selling student data through a subsidiary. Sallie Mae denies the allegations and vows to fight.
Lovable's Vibe-Coding App Now on iOS and Android
The app allows developers to vibe code web apps and websites on the go.
US Supreme Court Weighs 'Geofence' Warrant Use in AI Searches
The U.S. top court is expected to rule on whether to allow police to identify criminal suspects by dragnet searching the databases of tech giants.
Australia's New Law: Big Tech to Pay for News or Face 2.25% Tax
The more deals platforms make with media outlets, the less they pay. If enough agreements go through, that effective rate drops to 1.5%, which could generate between A$200 million and A$250 million back into Australian journalism.
Paragon Refuses to Aid Italian Spyware Investigation
Despite promising to help determine what happened with the hacks targeting journalists and activists in Italy, Israeli American spyware maker Paragon has reportedly not responded to authorities’ requests for information.
Amazon Introduces AI Audio Q&A for Product Pages
Amazon's new "Join the chat" feature lets you ask questions about products and receive AI-powered audio responses.
Google Expands Pentagon's AI Access After Anthropic's Refusal
After Anthropic refused to allow the DoD to use its AI for domestic mass surveillance and autonomous weapons, Google has signed a new contract with the department.
Match Group Invests $100M in Gay Cruising App Sniffies
The app is Match Group's newest attempt to get mobile users excited about online romance again.
Exploring AI Empathy: Teaching AI with Brain Signals
Podcast episode with Thorsten Zander, professor at Brandenburg University of Technology and co-founder of Zander Labs. He coined the concept of *passive brain-computer interfaces*: devices that read brain signals to decode a user's mental state, non-invasively and without any effort on their part. Covers: * What non-invasive brain-computer interfaces (BCIs) can actually pick up from brain signals, and why that's very different from reading your thoughts or internal monologue * The hardware and software breakthroughs that are finally making passive BCIs wearable and affordable * How continuous neural feedback could dramatically improve AI training compared to current methods based on human ratings * Why Thorsten believes passive BCIs may offer the most concrete path to solving the AI alignment problem * The risk of social networks exploiting unconscious brain reactions to manipulate people, and why regulation alone is unlikely to be enough
Arc Gate: AI Tool Achieves Perfect Safety Benchmarks
Benchmarked on 40 out-of-distribution prompts, indirect requests, roleplay framings, hypothetical scenarios, technical phrasings. The stuff that slips past everything else. Arc Gate: P=1.00, R=1.00, F1=1.00 OpenAI Moderation API: P=1.00, R=0.75, F1=0.86 LlamaGuard 3 8B: P=1.00, R=0.55, F1=0.71 Zero false positives. Zero misses. Blocked prompts average 329ms and never reach your model. Detection overhead is \~350ms on top of your normal upstream latency. Sits in front of any OpenAI-compatible endpoint. No GPU on your side. One env var to configure. GitHub: https://github.com/9hannahnine-jpg/arc-gate Live dashboard: https://web-production-6e47f.up.railway.app/dashboard Happy to answer questions.
AI-Driven Drug Discovery: DeepMind Spinoff Enters Human Trials
AI Driven Drug Discovery: DeepMind Spinoff Enters Human Trials The landscape of drug discovery is undergoing a significant transformation with the advent of AI …
Snabbit Secures $56M as On-Demand Home Services Boom
Snabbit now processes over 40,000 daily jobs and has cut costs sharply as it expands across cities and services.
Otter AI Adds Enterprise Search and Windows Note Capture
Otter is also releasing a new Windows app that can capture meeting notes without joining one
Golden Child's AI-Powered Dog Food Brand Raises $37M
Golden Child is launching with two "five-star" products: a fresh frozen meal system and, more intriguingly, a "drizzle." It has also raised $37 million in funding.
Red Hat's OpenClaw Now Safer with Tank OS Containers
Tank OS puts OpenClaw AI agents into a container that let's it run reliably and more safely, especially for those running fleets of them.
Neurable's Non-Invasive Mind-Reading Tech for Wearables
The startup specializes in "non-invasive" "mind-reading" tech—a kind of neural data collection that, its CEO hopes, will have all sorts of consumer applications.
YouTube Tests AI-Powered Search for Premium Users
YouTube is rolling out the new AI search feature to Premium subscribers in the U.S. on an opt-in basis.
Snapchat Launches AI Chat for Brand Interactions
Users will be able to chat with a brand's AI agent to do things like ask questions and get recommendations.
AI in Medicine: California's Tech-Driven Healthcare Shift
Hi everyone! My journalism professor is making us write a feature article with multiple interviews. The topic I got is the relationship between the healthcare and technology sectors in California. I am specifically focusing on how the push and pull between these two sectors is driving the rapid corporatization of healthcare. My article is supposed to explore how the expansion of tech-driven healthcare solutions, such as digital health, AI services, and venture-backed hospitals, is contributing to a healthcare system that increasingly puts profits over patient care. My draft is due this weekend, but 2 of my interviews ghosted me, so I need people to interview and some more ideas. If anyone is willing to give me their opinions on their experiences of AI in medicine or any ideas in the comments, that would be amazing. If any doctors or those involved in either sector would be open to being interviewed, please let me know! I would love the opportunity!
SpeakON Dictation Device Review: MagSafe Transcription for iPhone
This $129 device uses MagSafe to stick on the back of an iPhone to power transcription across apps.
Elon Musk's Latest on Transportation AI: TechCrunch Mobility
Elon Musk's Latest Advances in Transportation AI: Insights from TechCrunch Mobility In the ever evolving landscape of transportation, Elon Musk continues to pus…
Apple's Evolution Under Tim Cook: Challenges for New CEO
On the latest episode of Equity, we discuss how Apple has changed since Cook became CEO in 2011, and what challenges incoming CEO John Ternus will be facing.
Unusual Bay Area Home Sale Requires Anthropic Equity
Someone’s offering an unusual deal for a 13-acre property in Mill Valley, just north of San Francisco.
Truecaller's Growth Strategies Beyond India
As growth slows, Truecaller is leaning on subscriptions, business services, and new features to sustain momentum beyond India.
Amazon's New AI-Driven Podcast Monetization Strategy
Amazon's podcasting business seems to have transformed over the past six months.
Stanford Freshmen Inspired by AI Book to Rule the World
Can a book like this actually change anything? Or does the spotlight, as it always seems to, send more students racing to the place?
2025: Social Media Scams Cost Consumers $2.1B, FTC Finds
The agency reports that losses from social media scams have increased eightfold and that social media scams resulted in higher losses than any other method scammers used to contact consumers.
Letterboxd Seeks New Owner: Potential Buyers Emerge
Potential buyers of Letterboxd include Versant, the parent company of CNBC and MS NOW, and Hollywood media company The Ankler, according to Semafor.
AGI: The Dream of Tech World and Humanity's Future
What if they get their dream and the AGI, chooses general humanity above the elite.
Atech: Snap-Together Electronics via AI Chat
Snap-together electronics built from a chat
Data Center Demand Boosts Natural Gas Plant Costs 66%
Natural gas power plant costs have nearly doubled in two years and take 23% longer to build as data center electricity demand skyrockets.
Europe's Shift from US Software to Sovereign Tech
Governments across Europe are looking to rely less on American tech providers.
Skye's AI Home Screen App for iPhone Gains Investor Interest
Skye's new AI app attracted investors before it even launched — a sign of interest in a more AI-aware iPhone.
David Silver's Ineffable Intelligence Raises $1.1B for AI Innovation
Ineffable Intelligence, a British AI lab founded a mere few months ago by former DeepMind researcher David Silver, has raised $1.1 billion in funding at a valuation of $5.1 billion.
Chinese Hacker Xu Zewei Extradited to U.S. for COVID-19 Research Theft
Xu Zewei is accused of participating in a Chinese government hacking group that broke into thousands of U.S. organizations and stole COVID-19-related research.
OpenAI Allowed to Sell on AWS in Microsoft Deal
OpenAI has won major concessions from its largest shareholder, Microsoft, that will allow it to sell products on AWS, while Microsoft get more cash in a revenue-share agreement.
Spotify Expands to Fitness: Workouts, Playlists, and Peloton Classes
Spotify is adding fitness as its next major category, launching workout videos, playlists, and Peloton classes inside the app for free and Premium users.
OpenAI's AI-Powered Phone: Apps Replaced by Agents
The phone could go in mass production in 2028, an analyst says.