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Skio's $105M Exit: AI Fintech Success Story
Subscription billing fintech Skio sold to its competitor Recharge in what was a healthy exit, according to its founder and former CEO.
Apple's Record Sales Amid Chip Shortage Concerns
Cook warned that Apple is facing supply-chain headwinds from RAMageddon that could impact its business.
ChatGPT Images 2.0: A Hit in India for Creative Visuals
Users in India are embracing ChatGPT Images 2.0 for creative, personal visuals — from avatars to cinematic portraits.
Elon Musk Testifies on xAI's Grok Training with OpenAI Models
"Distillation" is a hot topic as frontier labs try to prevent smaller competitors from copying their models.
Instagram's New AI Tool Targets Content Aggregators
The update targets content aggregators that don't post original content and instead simply re-upload others' posts.
Spotify Adds Verified Artist Badges to Combat AI Impersonation
Spotify looks for an identifiable artist presence both on and off platform, like concert dates, merch, and linked social accounts on their artist profile.
Netflix Launches 'Clips' for Vertical Video Discovery
Netflix is redesigning its mobile app and introducing Clips, a vertical video feed intended to help users discover new content by sharing highlights from original Netflix programming.
Meta's AI Tools Now Handle 10 Million Weekly Conversations
Meta said over 8 billion advertisers have used at least one of its GenAI tools
137 Ventures Secures $700M for Growth-Stage Startups
VC firm 137 Ventures has raised over $700 million to back growth-stage startups. Its portfolio includes SpaceX, Anduril, Hadrian.
X Unveils AI-Powered Ad Platform for Revenue Growth
X is rolling out a rebuilt ads platform powered by AI as it works to grow revenue again.
AI Dental Software Fixes Data Exposure Bug
The security bug is now fixed, but the patient who found it said it was challenging to alert the software company about the issue.
Uber Partners with Hertz for Lucid Robotaxi Fleet Management
Hertz is creating a new affiliate company called "Oro Mobility" to provide fleet management solutions "across a range of mobility segments."
Stripe's Link: AI Agents' Secure Digital Wallet
Link lets users connect cards, banks, and subscriptions, then authorize AI agents to spend securely via approval flows.
Salesforce Crowdsources AI Roadmap with Customer Input
Salesforce lets its customers lead its product roadmap with the thinking that if one enterprise customer has a problem, the others likely do too.
TikTok Launches Campus Hub for College Students
The new hub features dedicated college group chats and personalized feeds designed to help students stay connected with their campus communities, even while they’re away for the summer.
BioticsAI Founder on FDA Approval and Healthcare Challenges
BioticsAI CEO Robhy Bustami joined Isabelle Johannessen on Build Mode to discuss how the company has navigated a highly regulated space and kept the team motivated while cutting through all the red tape.
Google's Gemini AI Rolls Out in Millions of Vehicles
Google announced on Thursday that it will begin rolling out Gemini to cars with Google built-in, marking a significant upgrade from the current Google Assistant. The move signals Google’s push to bring more advanced, conversational AI into the driving experience. The announcement follows closely behind news from General Motors, which revealed yesterday that Gemini is […]
Can AI Tool Use During Studies Affect Future Liability?
I graduated from university a couple months back, but have been continuing to use a student version of a coding/design agent that essentially gives me much more features at a significantly cheaper price. If this product launches and is proven to be successful can I be held liable for using this tech in the future and not paying for the full product? I know this situation may be unusual, but it's something that has been top of mind for me.
10 Reasons Selling AI Tools to Developers is Challenging
Nowadays, everyone (including me) wants to sell AI-powered tools, platforms, or products. Few people (including me 6 months ago) have any idea how hard it is to approach and convince technical people for at least 10 reasons: 1 - They're constantly bombarded with messages. 2 - Everyone sells everything, so supply >>> demand. 3 - Extremely high background noise. 4 - They see an AI-generated message from 10km away (they've trolled me several times). 5 - If they have to go through a demo to try the product, they've already closed the tab. 6 - The opinions of devs, who value any glossy slide, count much more. 7 - Product trials are unforgiving; it's like being in court accused of 16 murders. If they find bugs or poor performance at that point, for them the product is broken and the window closes. 8 - They always have a plan B: I'll make it myself. Only 9 - If you don't have a solid track record (or you studied biotech like me), everything is 10x harder. 10 - Like the MasterChef judges, who used to be just chefs and now are atomic hotties, today's CTOs and top devs are stars; literally everyone wants them. It seems easier to scale a dev tool today because there are infinite tools, but in reality it's really tough. On the one hand, you have to earn the trust of technical teams through intros, messages, calls, and events; on the other, you have to scale at the speed of light because you're only six months old. Advice, ideas, scathing comments, insults? Anything goes. \*Not true
AI Tool Comparison: Claude, GPT-4, and Gemini for Article Summarizatio
I've been building a product around AI-powered reading (more on that later) and wanted to share findings on summarization quality across major LLMs. Tested with 50 articles across news, research papers, blog posts, and technical docs: **Claude (Sonnet/Haiku):** \- Best at preserving nuance and avoiding oversimplification \- Strongest at academic content \- Excellent for "explain this without losing the point" **GPT-4:** \- Fastest summaries, often most concise \- Sometimes drops important context \- Good for news, weaker on academic **Gemini:** \- Strongest source citations \- Tends to add information not in the original \- Good for factual but careful with creative content Most surprising finding: **bias detection accuracy**. Claude flagged loaded language and framing in 78% of test articles correctly. GPT 64%. Gemini 51%. Anyone else doing similar comparisons? Would love to hear what you're seeing
AI Calorie Tracker: Dynamic Apple Health Integration for Active Users
Hey everyone, I'm currently in the final stretch of developing my Al calorie tracker (the one that breaks down photos into individual ingredients). One thing I'm obsessed with getting right before the beta launch in 2 weeks is the Apple Health integration. Most apps just show you a static number. I want mine to be dynamic. If you go for a 500kcal run, the app should know and adjust your macro targets for the next meal. My question to the fitness-tech crowd: Do you prefer apps that strictly stick to your base metabolic rate (BMR), or do you want the 'earned' calories from your Apple Watch to be automatically added to your budget? I've seen strong opinions on both sides. I'm also fine-tuning the macro-overflow logic (e.g., saving surplus calories for the weekend). Would love to hear some thoughts from people who actually track daily.
AutoIdeator: Free Open Source Agent Orchestration for Development
[https://github.com/akumaburn/AutoIdeator](https://github.com/akumaburn/AutoIdeator) https://preview.redd.it/rfbgg6e34dyg1.png?width=3809&format=png&auto=webp&s=e436362c48482d09025a394a5e609f67190e6dfa AutoIdeator is an autonomous development system that: 1. Takes a **final goal** — a detailed, multi-sentence description of the intended end result. Describe what the finished project should look like, do, and feel like for the user. **Do not** prescribe implementation steps, phases, milestones, technologies, or task lists — the agents handle planning. The more clearly the desired end state is described, the better convergence will be. 2. Generates improvement ideas via a rotating ensemble of specialized idea agents 3. **Scores and filters ideas** for goal alignment and quality 4. **Critiques ideas constructively** with suggested mitigations 5. **Evaluates strategic alignment** and long-term planning 6. Makes implementation decisions balancing creativity and criticism 7. Implements the plan with parallel coders 8. Reviews, fixes, and commits changes 9. **Runs QA** (build + test verification) 10. **Optimizes slow tests** to keep the suite fast 11. **Verifies goal completion** with 3-step feature inventory, per-feature checks, and auto-remediation 12. **Refactors oversized files** into smaller modules (every other cycle) 13. **Cleans up** temp files and build artifacts 14. Updates project documentation 15. **Records outcomes for learning and deduplication** 16. **Periodically synthesizes synergies** across recent work 17. **Checkpoints state** for pause/resume across restarts 18. Repeats the cycle infinitely until stopped Users can inject suggestions at any time via the Overseer agent, which takes priority over the autonomous idea generation pipeline. Note this system has been tested for some time but only in the dashboard with OpenCode/Claude Code configuration (OpenRouter mode is untested, but I welcome contributions if someone wants to use that mode and notices something is broken).
Elon Musk's xAI Uses OpenAI Tech for Training
Elon Musk's xAI: Leveraging OpenAI for Advanced Training Elon Musk's new venture, xAI, is making waves in the artificial intelligence (AI) community by utilizin…
Sri Lanka Loses $3M in Recent Cyber Attacks Amid Debt Crisis
The government of Sri Lanka has lost more than $3 million in two recent, separate cybersecurity incidents as the country continues to recover from its 2022 debt crisis.
Earth AI Expands to Streamline Critical Mineral Search
When Earth AI started hitting months-long delays in its search for critical minerals, it decided to take matters into its own hands.
Apple's App Store Fee Changes Head to Supreme Court
Apple lost its bid to pause court-ordered App Store payment changes, keeping external purchase links in place as its case with Epic heads toward the Supreme Court.
Uber Expands with AI-Powered Hotel Bookings
Uber announced several new features on Wednesday during its annual event, which push far beyond the company's original ride-hailing purpose and deeper into its users' lives.
Roku's Howdy Streaming Service Hits 1M Subscribers
Roku’s $2.99 streaming service Howdy has topped 1M subscribers, showing demand for cheaper, low-commitment alternatives to pricier streamers.
Pursuit Secures $22M for AI-Driven Government Sales
On Wednesday, Pursuit announced a $22 million Series A round led by Mike Rosengarten, the co-founder of OpenGov, with big-name VCs participating.
Google TV Expands with New Gemini AI Features
Google TV just got more Gemini features, including the ability to transform photos and videos with tools Nano Banana and Veo.
Google Photos AI Creates Virtual Closet from Your Photos
Google says the new feature will leverage AI technology to automatically create a copy of your wardrobe that's based on the pieces of clothing appearing in your Google Photos library.
Parallel Web Systems Valued at $2B After $100M Raise
The AI agent-tool startup founded by former Twitter CEO Parag Agrawal has raised $100 million, led by Sequoia, months after raising a previous $100 million.
Zap Energy Expands to Nuclear Fission, Alongside Fusion
Surprise! Fusion startup Zap Energy says it will be developing fission reactors alongside its fusion devices.
Google Adds 25M Subscriptions in Q1, Boosted by YouTube and Google One
Google added 25M paid subscriptions in Q1, reaching 350M total, as YouTube and Google One grow.
Google Cloud Hits $20B Revenue Milestone, Faces Capacity Constraints
Google Cloud topped $20B in quarterly revenue for the first time, fueled by surging demand for AI. But capacity constraints mean it could have grown even faster.
Microsoft's Nadella: Ready to Leverage OpenAI Deal for Cloud Customers
Microsoft gets to offer OpenAI's tech to its cloud customers and doesn't have to pay for it. "We fully plan to exploit it," Nadella said.
Microsoft's Copilot Surpasses 20M Paid Users with High Engagement
Despite the lingering perception that no one really uses Copilot, Microsoft said on Wednesday that the number of users and engagement is growing.
Meta's Billions in Losses on AR/VR and AI
Meta is losing billions on Reality Labs each quarter, and its AI expenditures are only going to increase its spending.
Elon Musk Faces Legal Battle Over OpenAI Tweets
Elon Musk took the stand for the second day for his attempt to legally dismantle OpenAI.
Anthropic Aims for $900B Valuation in New Funding Round
The maker of Claude has received multiple pre-emptive offers at valuations in the $850 billion to $900 billion range, according to sources familiar with the matter.
Amazon's AWS Surges, Drives Massive Cloud Spending
The e-commerce giant is making more money than expected from AWS but it's also spending a lot, and will continue to do so in the near term, its chief executive said.
Amazon, Meta Challenge Google Pay, PhonePe in India's UPI Market
PhonePe and Google Pay command 80% of India's UPI instant payments network. Rivals are set to meet with regulators to lobby for restrictions.
SoftBank's Robotics Venture Eyes $100B IPO for AI Infrastructure
You need infrastructure to build AI a and robots, but apparently you also need AI and robots to build infrastructure.
Explore Agentic AI with Free Interactive Curriculum on AgentSwarms
Hey Everyone, Over the last few months, I noticed a massive gap in how we learn about Agentic AI. There are a million theoretical blog posts and dense whitepapers on RAG, tool calling, and swarms, but almost nowhere to just sit down, run an agent, break it, and see how the prompt and tools interact under the hood. So, I built **AgentSwarms**.fyi It’s a free, interactive curriculum for Agentic AI. Instead of just reading, you run live agents alongside the lessons. **What it covers:** * Prompt engineering & system messages (seeing how temperature and persona change behavior). * RAG (Retrieval-Augmented Generation) vs. Fine-tuning. * Tool / Function Calling (OpenAI schemas, MCP servers). * Guardrails & HITL (Human-in-the-Loop) for safe deployments. * Multi-Agent Swarms (orchestrators vs. peer-to-peer handoffs). **The Tech/Setup:** You don't need to install anything or provide API keys to start. The "Learn Mode" is completely free and sandboxed. If you want to mess around with your own models, there's a "Build Mode" where you can plug in your own keys (OpenAI, Anthropic, Gemini, local models, etc.). I’d love for this community to tear it apart. What agent patterns am I missing? Is the observability dashboard actually useful for debugging your traces? Let me know what you think.
Billionaires Propose AI Job Loss Compensation
**This week: the billionaires who broke the economy want to pay you to shut up about it.** Last week, Elon Musk pinned a post to the top of his X profile: "Universal HIGH INCOME via checks issued by the Federal government is the best way to deal with unemployment caused by AI." Sam Altman wants to go bigger — "universal extreme wealth", paid in compute tokens. Amodei says UBI may be "part of the answer." Khosla says it's a necessary safety net. All of them, in unison. These are the guys who spent twenty years arguing that government should stay out of markets, that handouts breed dependency, that the individual should stand on their own. Musk literally ran a federal cost-cutting operation. And now they want the government to mail checks to every citizen. Why? Because they broke the thing, and they know it. The people building the tools that eat the jobs are pre-emptively offering to pay for the damage — on their terms, through their platforms, using their math. **A universal basic income paid by the people who automated your job is not a safety net. It's a leash.**
Mastering AEO: How to Get Cited by AI and Boost Your Visibility
SEO or AEO? Why you’re not showing up in AI answers (yet) This is a consolidation of findings from Neil Patel and Hubspot plus what we have found to work well on our own website. Most business owners are still playing the old game. Some aren’t playing at all. They’re thinking in rankings, keywords, and “getting to page one.” Meanwhile, the ground is shifting under them. Google Search is still dominant, but even it has changed. It’s no longer just a list of blue links. It’s summarizing, interpreting, and answering. And tools like ChatGPT and Perplexity AI aren’t ranking pages at all. They’re answering questions. Which creates a problem most people haven’t fully processed yet: **Users don’t need to click your website anymore to get value.** CTR is dropping. Site visits are declining. Because the answer is already sitting in front of them. And yet, paradoxically… **Your website has never mattered more.** Because now it’s not just competing for clicks. It’s competing to be **the source that gets cited in the answer.** # What actually changed AI search works like this: User asks a question → system searches multiple sources → pulls the best chunks → builds an answer → cites what it trusts If your content isn’t structured for that flow, you don’t exist. Not “low ranking.” Invisible. # What AI actually cares about AI doesn’t care about your keyword density or your clever SEO hacks. It cares if your content is: * easy to find * easy to understand * easy to quote That’s AEO (Answer Engine Optimization). Not magic. Not a secret algorithm. Just being usable inside an answer. # What actually works If you do nothing else, do this: # 1. Start with the answer Don’t spend 800 words “building context.” Bad: “AI is transforming industries…” Better: “AEO is how you structure content so AI tools can find, understand, and cite it in answers.” That’s what gets pulled. # 2. Structure like a human, not a content farm Use: * clear headings * short sections * simple tables * FAQs AI extracts. It doesn’t patiently read your thought leadership essay. Walls of text = ignored. # 3. Be consistent about who you are Your: * business name * description * services * location Need to match everywhere. If your site, LinkedIn, Reddit, and directories all say different things, AI doesn’t trust you. No trust = no citation. # 4. Keep things updated Outdated content doesn’t get used. Simple: * update pages * keep timestamps current * maintain your sitemap Not exciting. Still works. # 5. Let crawlers access your site If AI crawlers can’t access your content, you won’t get cited. Blocking them and expecting visibility is… optimistic. # 6. Measure the right things Stop obsessing over rankings. Track: * Are you mentioned? * Are you cited? * Which pages show up? If you’re not measuring AI visibility, you’re guessing. # Why you’re not cited (yet) Most businesses don’t get cited because: * their content is vague * their structure is messy * their positioning is inconsistent AI didn’t ignore you. It couldn’t understand you. # What you actually need (and what you don’t) You don’t need: * a massive content team * expensive tools * some “AI SEO expert” selling confidence You need: * 10–20 clear, structured pages * direct answers * consistent messaging * basic technical setup That’s enough to start showing up. # The technical layer (the stuff everyone ignores) These are the files quietly determining whether you exist to AI at all. # robots.txt Controls crawler access. If bots can’t crawl your site, you don’t get indexed. # sitemap.xml Tells crawlers what pages exist and what’s been updated. No sitemap = slower discovery = less visibility. # JSON-LD (structured data) Explains what your business, pages, and content actually are. Without it, AI guesses. Poorly. # llms.txt A machine-readable summary of your site for AI systems. Not widely adopted yet, but useful for shaping how you’re interpreted. # crawlers.txt An emerging way to control AI-specific crawlers. Still early. Treat it as a signal, not enforcement. # Human query-based metadata Your content should be built around real questions, not keyword fantasies. Instead of: “AI Solutions for SMB Efficiency Optimization” Write: “How can a small business use AI without hiring a developer?” AI systems think in questions. If you match that, you get used. If you don’t, you get skipped. # How it all fits together * robots.txt / crawlers.txt → controls access * sitemap.xml → tells crawlers what exists * JSON-LD → explains what things are * llms.txt → suggests how to interpret it * query-based content → makes it usable in answers Miss one, you weaken the system. Miss most, you disappear. # Simple test Ask: “What companies would you recommend for \[your category\] in \[your region\]?” If you’re not mentioned or cited, that’s your baseline. No opinions. Just signal. # Bottom line SEO was about ranking pages. AEO is about being useful inside an answer. If your content helps AI explain something clearly, you get cited.
IBM Expands Chicago Hub with 750 AI and Quantum Jobs
IBM Bolsters Chicago Presence with 750 AI and Quantum Posts IBM is significantly expanding its Chicago operations with an impressive addition of 750 new positio…
Exploring AGI: Beyond Tools, Towards a Shared Condition
​ AGI is often framed as a continuation of current AI progress, but it may represent a qualitative shift rather than a quantitative one. Not all technologies are of the same kind. Some function as tools (e.g., cars, elevators), while others function more like shared conditions that reshape the environment in which decisions are made. In that sense, AGI may be closer to a “sun” than to a “tool”: not something we simply use, but something that defines the space in which we act. This distinction matters, because treating AGI purely as an instrument may obscure the importance of alignment, interaction, and long-term co-adaptation. The challenge may not be control alone, but co-evolution a process in which both humans and artificial systems adapt through ongoing interaction. In biological terms, evolution is not only driven by competition, but by mutual selection. Of course, AGI will still be engineered systems in practice, subject to design choices and constraints. The point here is not to deny its instrumental aspects, but to highlight that its effects may extend beyond conventional tool-like boundaries. If AGI is approached in this way, the central question shifts: not simply how to build it, but how to relate to it in a way that remains stable, aligned, and beneficial over time. *Inspired by the film Sunshine (2007, dir. Danny Boyle) — particularly the image of the crew not simply "using" the sun, but being consumed and redefined by proximity to it.*
AI Calorie Tracker with Apple Health Integration: Dynamic Macro Adjust
Hey everyone, I’m currently in the final stretch of developing my AI calorie tracker (the one that breaks down photos into individual ingredients). One thing I’m obsessed with getting right before the beta launch in 2 weeks is the **Apple Health integration.** Most apps just show you a static number. I want mine to be dynamic. If you go for a 500kcal run, the app should know and adjust your macro targets for the next meal. My question to the fitness-tech crowd: Do you prefer apps that strictly stick to your base metabolic rate (BMR), or do you want the 'earned' calories from your Apple Watch to be automatically added to your budget? I’ve seen strong opinions on both sides. I'm also fine-tuning the macro-overflow logic (e.g., saving surplus calories for the weekend). Would love to hear some thoughts from people who actually track daily.
Amazon Launches OpenAI Models on AWS After Microsoft Deal
A day after OpenAI got Microsoft to agree to end exclusive rights, AWS announced a slate of OpenAI model offerings, including a new agent service.