❕ China enforces AI content labeling

Starting September 1, China requires all AI-generated content from text and images to audio and video to be labeled. Platforms must apply both visible tags and hidden watermarks or metadata.

🔸 WeChat, Douyin, Weibo and RedNote have already rolled out the rules
🔸 Users must disclose AI use or risk account bans
🔸 Weibo now allows people to report posts without AI tags

For startups and creators this sets a precedent: AI output is now regulated at the content level, not just the model level.

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📊 How startups feel in 2025

Mercury surveyed 1,500 founders and the results paint a mixed but telling picture of today’s startup economy.

🔸 87% feel more confident than in 2024, only 3% say things are worse
🔸 Startups with AI are far more optimistic (93% vs 71%)
🔸 27% raised over $5M, often combining VC with loans, grants, or RBF
🔸 61% are hiring, but among $5M+ revenue companies there are no solo founders
🔸 80% expect costs to rise in 2025, mostly due to AI and automation

AI has shifted from optional to required, funding sources are diversifying beyond pure venture, and teams are the real bottleneck to scale.

Optimism is back, but founders who overextend on AI spend or inflate metrics may find 2025 just as risky as 2022.

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💡A new culture in Silicon Valley

In past decades, "hustle culture" was optional. Today for 18–25 year olds in the Valley it has become the norm. Bars, drugs, and hookups are replaced with 12-hour workdays, 6–7 days a week.
Not grinding is what’s “uncool.”

This isn’t about a few outliers, it’s widespread and culturally reinforced. It means this generation may achieve far more than those before them.

The open question is what the long-term cost will be to health and psychology.
Or maybe that’s just how we justify not working as hard.

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📞 Assort Health raises $26M to automate clinic calls

Assort Health is betting that millions of Americans will still pick up the phone to book a doctor. The startup built a generative AI platform that replaces human operators, handling patient calls and syncing them directly into clinic schedules and EMR systems.

🔸 Already live with 50+ clinics
🔸 Works 24/7, no apps required, just a phone number
🔸 Cuts admin load and reduces errors
🔸 Just closed $26M at a $750M valuation

The catch: phone-based scheduling is a shrinking channel. In cities, apps and AI agents already handle bookings. The long-term question is whether Assort is tapping into a sticky, underserved demographic or simply cashing in on AI hype before the phone goes extinct.

Would you call this smart timing or a misaligned bet on a dying habit?

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📊 Where the money flows in US startups

Crunchbase compared startup funding by state in 2025, and the picture is one-sided. California has pulled in well over $100B already, leaving New York, Massachusetts, and Texas far behind.

For founders chasing capital, the US map is simple. There’s California and then everyone else.

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🤖 Figure teaches Helix to load a dishwasher

Figure’s humanoid model Helix is showing how far general-purpose robotics can go. The same system that folded towels and sorted packages now loads dishwashers - no new algorithms, only new data.

🔸 Handles stacked plates, glasses, cluttered states
🔸 Uses two arms in sync for fragile reorientation
🔸 Recovers from slips and collisions without breaking flow
🔸 Learns new skills incrementally across domains

Loading a dishwasher might sound simple, but for robotics it combines perception, precision, and adaptability. Helix’s progress is another step toward humanoids that scale beyond demos into real-world use.

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🧮 Solve your math in a few clicks

Mathos is a simple helper for students that turns tough problems into clear, visual explanations.

🔸 Covers algebra, geometry, trigonometry, linear algebra, calculus, probability, and statistics
🔸 Accepts text, photos, PDFs, or voice input
🔸 Shows step-by-step solutions and builds graphs for clarity
🔸 Free to use

If you are buried under problem sets, this will save hours.

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🚕 Tesla opens Robotaxi to the public

Tesla has launched its Robotaxi app for iPhone users, letting anyone join the waitlist for self-driving rides. Until now, access was limited to influencers and celebrities.

🔸 Service currently works only in Austin
🔸 All rides still have a human safety observer in the passenger seat
🔸 In Silicon Valley, Tesla is testing a different Uber-style format with a driver behind the wheel overseeing the system

The move marks Tesla’s first real step toward scaling autonomous ride-hailing beyond PR stunts.

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🗣️ Altman vs Musk - the saga continues

In a new interview, Sam Altman was asked when he chose the world over corporate advantage.

His answer:

Well, we still haven’t added sex avatars to ChatGPT.

The rivalry between Altman and Musk keeps delivering some of the best tech one-liners. Honestly, hard to imagine a better duel than these two.

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🤖 Teaching a robot to ride, jump, and flip

At the RAI Institute, researchers are building the Ultra Mobility Vehicle (UMV), a bike-like robot designed to combine the speed of wheels with the agility of legs. The goal: give machines athlete-level movement through AI and reinforcement learning.

🔸 The robot’s lower half is a carbon fiber bike frame, while the upper “head” holds motors, compute, and power for jumps and flips
🔸 It weighs ~23 kg, can extend from 80 cm to 152 cm, and is engineered to survive crashes and rough landings

🔸 Sensors include IMUs, LiDAR, joint encoders, and cameras to track terrain and maintain balance

🔸 Reinforcement learning in simulation trains the robot for stunts like wheelies, continuous hopping, and one-meter flips

🔸 The team tackles the “sim-to-real gap” by randomizing parameters in training and modeling physical systems like motors and batteries

By blending robotics, AI, and athletic intelligence, UMV hints at machines that could one day navigate extreme terrain as effortlessly as human trial bikers. The next frontier: chaining skills into complex autonomous sequences.

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🛠 Build your own internet stronghold

A full toolkit of guides to help you become a truly independent internet user.

🔸 Launch a website on your own domain for free in just a few hours
🔸 Set up a private mail server and ditch Gmail
🔸 Run your own chat, social network, streaming platform - even a Monero node

Take control and build a fortified corner of the web.

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🦷 Japan begins human trials for tooth regrowth drug

Japanese researchers have started Phase 1 trials of TRG-035, a drug that could regenerate lost human teeth. Conducted at Kyoto University Hospital, the study is a major step toward regenerative dentistry.

🔸 TRG-035 blocks the USAG-1 protein, reactivating dormant tooth buds
🔸 Early animal trials in mice, ferrets, and dogs showed successful new tooth growth
🔸 Human trials involve 30 adults missing at least one tooth, testing safety and dosage
🔸 Potential use cases include congenital tooth agenesis in children and age-related tooth loss
🔸 Commercial availability is projected around 2030 if trials succeed

If proven safe and effective, TRG-035 could transform dental care - shifting from implants and dentures to natural regrowth.

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🧠 Why LLMs hallucinate, according to OpenAI

OpenAI just published a rare research piece on one of the hottest issues in AI: hallucinations. The takeaway - they’re not mysterious at all, but a natural byproduct of how we train and test models.

🔸 Pretraining phase: models are forced to always predict the “most likely” next token. Saying “I don’t know” isn’t an option, and there’s no penalty for making things up.
🔸 World randomness: some facts (like birthdays or serial numbers) are inherently unpredictable. Models can’t “learn” them.
🔸 Benchmarks: most evals score wrong and skipped answers the same — 0. This incentivizes guessing over admitting uncertainty.
🔸 Garbage In, Garbage Out: data errors inevitably feed into outputs.

OpenAI’s fix? Change evaluation itself. Add “I don’t know” as a valid response, and reward honesty over confident fiction. With confidence thresholds (e.g. only answer if >75% sure), models would learn that admitting uncertainty beats hallucinating.

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🗂 72 AI tools in one cheat sheet

A fresh list is making the rounds on Twitter — 72 of the most useful AI services across key categories:

🔸 Image generation
🔸 Video generation
🔸 Text writing
🔸 Research & analysis

A handy one-stop cheat sheet for anyone working with AI. Worth saving.

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💼 OpenAI to launch AI-focused jobs platform

OpenAI has announced OpenAI Jobs Platform, a hiring service where companies can find talent skilled in working with AI - from beginners to expert prompt engineers.

🔸 Platform will match business needs with candidates’ AI skills
🔸 Job seekers can take OpenAI’s own certification exam directly inside ChatGPT via Study mode
🔸 Official launch is planned for 2026

A move that could make OpenAI not just a model provider, but also a gatekeeper for the AI labor market.

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💻 Turn any repo into an AI prompt

GitIngest lets you feed an entire GitHub repo into an LLM in seconds.

🔸 Drop in a repo link and wait a moment
🔸 Get back a clean, structured prompt with the code and files
🔸 Edit it to trim noise and keep only what matters

A neat shortcut for devs who want their AI to grok a codebase fast.

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