Parthiv

BREAKING: First-Ever Full Tour of Figure's Humanoid HQ CEO Brett Adcock Exclusive look through every department on their San Jose campus: BotQ Factory, Testing, Design, Demos & more. Brett walks us through how Figure is built: - System integration lab: where robots are stress-tested with software faults & physical pushes - Helix AI: team floor where the controls & neural network engineers train the vision-language-action model that runs onboard every Figure robot - Reinforcement learning & stability testing: where Figure demos the Vulcan project — surviving a lost knee mid-task - Home: environment where Figure 03 autonomously tidies a living room using their Helix neural network (no teleoperation) - BotQ: manufacturing facility where heads, batteries, and limbs come together on the assembly line, including the custom-built battery line & end-of-line burn-in bays - Industrial design studio: (opened publicly for the first time) housing every generation of Figure robot ever built, including: Figure 01 with its Frankenstein forearms, Figure 02, & the sleek Figure 03 that recently appeared at the White House, plus the evolution of Figure's hands & feet Brett shares why he believes humanoid robots may achieve AGI before any other form factor, why Figure pivoted entirely from hand-coded controls to neural networks, & teases that Figure 04 will be their "iPhone 1 moment." This was so much fun! Big thank you to Brett & the team at Figure for opening the doors for us! @adcock_brett @Figure_robot 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Inside Figure’s Humanoid Campus (00:48) The humanoid factory (03:18) First humanoid guest at the White House (05:29) Controlling a robot with infinite movements (10:46) The truth about robot failures (13:00) Attacking a humanoid robot (testing responses) (16:12) Building a general purpose robot (23:05) The "Never Fall" protocol (28:56) Is the home robot teleoperated? (33:36) Leasing a 24/7 robot (35:01) Can a humanoid build a real car? (43:32) From flying robots to humanoids (45:59) The hidden path to physical AGI (56:21) Figure's secret design studio (01:00:44) Figure 4: The biggest leap in robotics (01:06:25) Training robots in spandex (01:10:26) Westworld, TIME Magazine, & Deadmau5

If you think AI replaces software engineers, here’s a quick thought experiment. Imagine you’re a life sciences company. 10 years ago you want to invest heavily in lab automation, processing data at scale, and other software. You look at the cost of doing so and realize you can’t compete with tech for as many engineers as you need, so you pare down your goals and do what you can. Every new software project has a fixed cost of a certain sized team, so you can only do so much given budgets, ability to compete for talent, and other trade offs. Now, AI comes along. And all of a sudden you have the *exact same* output tokens as the best tech companies in the world. Your engineers are using the same AI models as the tech industry, which means you have just boosted your engineering team by a some meaningful amount, while also neutralizing your differences with tech. Do you continue with your pared down approach, or do you start to hire more engineers because each engineer is 2X or 5X more capable than before? In almost every company I’m talking to, they’re doing the latter. Now extrapolate this to every bank, manufacturer, industrial company, retailer, and on and on. And extrapolate it not to just large enterprises, but also every SMB up and down the stack of these value chains. Oh, and also extrapolate this to other job functions, not just engineers. Resource scarce domains in marketing, legal, finance, design, and so on. If you’re wondering why new jobs show up because of AI this is the reason. Any other view of what happens doesn’t contemplate the variety of unmet needs there are in the economy.

@DILIPKUMAR9990 @BhojpuriQUEEN @changu311 @amritabhinder @iSinghApurva @AdityaRajKaul @MrsKashyap_ @RDXThinksThat @meriteshkashyap @activistritu heartbreaking...💔💔

एक माँ ने अपनी जान की परवाह किए बिना अपने बच्चे को सीने से लगाकर आख़िरी सांस ली... लाइफ़ जैकेट पहने होने के बावजूद वो पानी की गहराइयों से लड़ न सकी, लेकिन अपने बच्चे को आख़िरी पल तक सुरक्षित रखने की कोशिश करती रही. ये सिर्फ एक हादसा नहीं, ये माँ के प्यार की वो मिसाल है 1/1

you can outsource your thinking but you cannot outsource your understanding

Introducing Grader: the world's first AI CMO for restaurants. It’s helped us drive over $1 BILLION in sales for our customers. Grader outperforms human marketing teams. See how:

Q1 earnings are in: 2026 is off to a terrific start. Our AI investments and full stack approach are lighting up every part of the business: Search queries are at an all-time high with AI continuing to drive usage. Google Cloud revenue grew 63%, Gemini models have incredible momentum, and it was our strongest quarter ever for consumer AI subs, driven by @GeminiApp. Thanks to our partners + employees around the world. Much more to share on our earnings call in 20 minutes… and at Google I/O in 20 days!

This is a masterclass in how LLMs are trained and served - on the blackboard

This guy built a working Ironman suit in his garage Sound on 📹 Alex Lab

Steve gave this lecture at MIT Sloan in spring 1992. He had been fired from Apple seven years earlier and was running NeXT, a company burning $40 to $66 million a year selling premium black workstations almost nobody bought. The lecture is the operating manual for the next 30 years of Apple, written four years before he had any idea he’d ever go back. Listen to what he says about manufacturing. He describes a JIT factory at NeXT with zero warehouses. Parts come in, get delivered to the point of use on the floor, and that’s it. No outgoing warehouse either. In 1992, this was contrarian. Six years later, Tim Cook joined Apple and ran the same playbook. Apple’s supply chain became the most efficient in the history of consumer electronics. Every iPhone since 2007 ships on that chassis. Listen to what he says about consultants. “A mind is too important to waste.” His argument is that without owning a decision over a few years and accumulating scar tissue, you learn a fraction of what’s possible. When he returned to Apple in 1997, he ran the company with effectively zero strategic consulting work. The big calls were made internally. Listen to what he says about hiring. He tells the room he sometimes spends a year and a half pulling someone out of HP before they say yes. The team he built at NeXT included Avie Tevanian, Bertrand Serlet, Jon Rubinstein, and Tony Fadell. Every one of them came back to Apple with him in 1997. Tony built the iPod. Rubinstein ran hardware. Tevanian and Serlet built OS X. Listen to what he says about software. He’s pitching NeXTSTEP, the operating environment NeXT had just ported to Intel. He says it lets you build apps five to ten times faster than anything else. Four years later Apple bought NeXT for $429 million for that exact codebase. NeXTSTEP became Mac OS X in 2001. OS X became iOS in 2007. iOS runs on 2.2 billion active devices today. The audience asked him what he learned at Apple. He paused, then said he now takes a longer-term view on people. “We’re building a team here and we’re going to do good stuff for the next decade.” Tim Cook joined in 1998 and ran operations for 13 years before becoming CEO. Jony Ive ran design at Apple for 27 years. Phil Schiller ran marketing for two decades. NeXT had accumulated $273 million in losses by the time Apple bought it. The company was, by every public metric, a failure. Steve walked into that lecture hall having spent seven years being wrong in front of everyone, and used the hour to lay out the playbook that would build the most valuable company in history. The MBAs in that room had front-row seats to the comeback four years before it started.

For our last Cheeky Pint episode this season, @evanspiegel joins me to discuss the "crucible moment" at Snap. We cover the shift from smartphones to AR glasses, why he thinks VR is antisocial, how creative culture at Snap works, and why Norway is Snapchat-obsessed.

@vivekraju93 Congratulations @vivekraju93 to you and your family 🎉🎉🎉🎉

Became boy dad. New happiness level unlocked in life

@priteshlakhani You can also check petpooja biometric device, works well for my use case

For $128,000 you can buy a Jetson ONE, take off from your backyard, and never need a pilot's license. Every spec on it is reverse-engineered from a single FAA regulation. Part 103 caps ultralight empty weight at 254 pounds. Jetson built theirs at 189. Part 103 caps level flight at 55 knots. Jetson tops out at 63 mph, exactly that. Part 103 allows one occupant. Jetson built one seat. Stay inside those lines and the FAA does not classify what you are flying as an aircraft. No pilot's license. No medical certificate. No registration. No regulatory oversight of the design. No regulatory oversight of operator competency. That is the entire business model. The $128K buys you exemption from being a pilot. You can see it in the rest of the spec sheet. 13.5 kWh battery for 17 minutes of flight. Open cockpit, helmet required. Daylight only, uncongested areas, away from airports. Every line is a Part 103 rule rendered as hardware. Build it any other way and it stops being an ultralight, which means type certification, which means five years and nine figures before you ship a single unit. Joby has been at it since 2009. Archer since 2018. Combined they have raised over $4 billion building certified eVTOLs. Neither has carried a paying passenger. Jetson started shipping in 2024. Sold out through 2026. Deliveries pushed to 2027. Palmer Luckey took the first production unit. MrBeast flew one down the California coast. The whole point of buying a Jetson is the permission slip that comes with it. Everything else is just hardware.

🚀Meet Carnice-V2-27b🚀 → Carnice is a 27 billion parameter model capable of beating models 10x the size in Hermes-agent, fully open-source and built on top of Qwen3.6-27B →Build to fit on Consumer GPU on a 3090+ to run locally🔥 →Carnice-V2-27b is the successor of Carnice-27b trained on more and better data Download it here: huggingface.co/kai-os/Carnice… Download GGUF here: huggingface.co/kai-os/Carnice… thanks to @NousResearch @LambdaAPI for making this possible.

DEEPSEEK-V4 IS RELEASED

🚀 Meet Qwen3.6-27B, our latest dense, open-source model, packing flagship-level coding power! Yes, 27B, and Qwen3.6-27B punches way above its weight. 👇 What's new: 🧠 Outstanding agentic coding — surpasses Qwen3.5-397B-A17B across all major coding benchmarks 💡 Strong reasoning across text & multimodal tasks 🔄 Supports thinking & non-thinking modes ✅ Apache 2.0 — fully open, fully yours Smaller model. Bigger results. Community's favorite. ❤️ We can't wait to see what you build with Qwen3.6-27B! 👀 🔗👇 Blog: qwen.ai/blog?id=qwen3.… Qwen Studio: chat.qwen.ai/?models=qwen3.… Github: github.com/QwenLM/Qwen3.6 Hugging Face: huggingface.co/Qwen/Qwen3.6-2… huggingface.co/Qwen/Qwen3.6-2… ModelScope: modelscope.cn/models/Qwen/Qw… modelscope.cn/models/Qwen/Qw…

The Beijing Humanoid Half Marathon (21.1 km) just concluded! The humanoid winner was significantly faster than the top human finisher. - 1st place: Monkey King Team – Honor Lightning robot, 50 min 26 seconds - 2nd place: Mixue Ice City Team – same Honor Lightning robot, 50m 56s - 3rd place: Spark Team – same Honor Lightning robot, 53m 01s Another Honor Lightning robot finished the fastest, in 48m 19s, but was penalized (1.2x the finish time) for being teleoperated and missed the podium. The human winner finished in 1h 07m 47s.

petpooja is such a goated name for a restaurant platform

@threeoneonetwo Khushi ki baat for @parthiv645