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Welcome to The Robot Almanac, Morgan Stanley’s new series exploring the rise of robotics and physical AI through 2050. Watch the introduction now and subscribe for future episodes.

Comparison between GPT-Images 2.5 vs GPT-Images 2.0 Here's the prompt: "Animate the supplied pixel-art heroine in one continuous 8-second side-view shot. Preserve her exact design, colors, proportions, crisp pixels, and outlines. Lock the camera and pale blue-gray background. Keep her full body near center, facing right, with no more than 25% horizontal travel. From 0–2.5s, run mostly in place with alternating strides and arm pumps. From 2.5–4.5s, perform one two-foot jump and land crouched. From 4.5–6.5s, perform one full forward ground somersault: hands down, tuck, roll over the shoulders, feet over head, and land on both feet. From 6.5–8s, rise into a balanced ready pose. Animate at exactly 6 FPS with 167ms frame holds, normal speed, and no interpolation, blending, optical flow, or blur. On every frame, shift the whole sprite slightly and unpredictably on both axes to create strong constant jitter, especially in the final pose. Only the heroine moves; the camera and background remain still. No cuts, cartwheels, aerial flips, scene changes, text, particles, weapons, duplicates, audio, 3D, color flicker, morphing, or design drift."

Open router for chips is a $10B+ company waiting to be built Nobody moves custom inference workloads off Nvidia because porting to AMD, Cerebras, Etched, etc. is painful But with frontier models now you could build a pipeline for translating workloads from one chip to another When that starts happening reliably there there will be a rise of multi-chip neoclouds. Neoclouds won’t buy non-Nvidia chips today because developers don’t use them. That will change once you eliminate the code compatibility problem and performance is the driving factor If you build it, the play is either open source it from day 1 and become a strategic acquisition target for a big neocloud, or keep it private and build your own cloud, becoming the de facto multi-chip provider

🏆Going above and beyond pays off in the Nest! We are SUPER PROUD of these scholars for scoring 100% on the "Weekly ELA and Math Challenge!" @DrShemon @JMCSchools @suptking #BestInTN# #FutureLeaders# #Empower# #RiseAboveExpectations#

Jones rises on the Leaderboard 📈 With this block, Jonquel Jones passes Taj McWilliams-Franklin on the all‑time blocks list, moving into 13th place! GSV-NYL | Prime Video Tap to watch:

ZERO ALPHA Research Preview | Reframing NVDA NVIDIA’s latest earnings report is the trigger event for a new round of deep research. A company already among the largest in the world just delivered 106% year-over-year revenue growth, with Data Center revenue up 117%. What is striking is not simply that NVIDIA beat expectations again, but that its core business has returned to a doubling growth rate from an already enormous base, even as AMD GPUs, hyperscaler-designed chips, and custom AI accelerators continue to enter the market. That prompted us to go back and re-examine NVIDIA’s full growth trajectory since 2023. When revenue growth, earnings growth, stock-price appreciation, and P/E are viewed together, a very different pattern begins to emerge. The first NVIDIA spring was largely top-down. The market recognized the potential of generative AI first, the stock price moved ahead, and earnings later caught up. The second spring now looks increasingly bottom-up. Revenue growth re-accelerated from: 56% → 62% → 73% → 85% → 106% while valuation multiples moved lower rather than higher. In simple terms: First Spring: P led E. Second Spring: E is beginning to lead P. This earnings report therefore may represent more than another earnings beat. It may be a signal that NVDA itself needs to be reframed. It also raises a broader question: What actually defines a true mega-cap growth stock? A high P/E alone does not define growth. The rarest structure may be a company that is already enormous, still grows its core business near 100%, generates earnings faster than its stock price rises, avoids excessive valuation expansion, and continues to create new TAM. Applying this framework to AMD, MU, SNDK, LITE, ALAB, DELL, and the hyperscalers makes the leadership hierarchy increasingly clear. Many of them have strong growth, but each still carries a weakness in valuation, cyclicality, pricing dependence, platform control, or growth durability. NVDA currently presents a more unusual combination. More importantly, at least four additional growth engines are still developing: Pricing Power Supply Efficiency Open Models Inference Specialization If these continue to develop, today’s NVIDIA may not yet represent the peak of this second growth cycle. And NVIDIA’s second spring may not belong to NVIDIA alone. Memory and storage, optical networking, and AI data-center operators could all benefit if another AI infrastructure expansion cycle is now beginning. ZERO ALPHA will therefore use this earnings report — a mega-cap company returning to 100%+ core growth — as the starting point for a six-part NVDA Research Note series: 1/6. NVDA: The Second Spring — From P Leading E to E Leading P 2/6. NVDA: What Defines a True Mega-Cap Growth Stock? 3/6. NVDA: Why It Is Still in Its Prime, Not Near the Peak 4/6. NVDA: Four New Growth Engines — How Far Can the Second Spring Go? 5/6. NVDA: Why Leaders Lose Leadership — Lessons from Intel, Tesla, and AMD 6/6. NVDA: Will the Second Spring Reignite the Entire AI Infrastructure Chain? Each note will focus on one independent question and can be read on its own. ZERO Insight The most important message from this earnings report may not be that NVIDIA beat expectations again. It may be this: When a company already this large returns to 100%+ core growth while trading at a much lower P/E than during its first AI explosion, what needs to be revalued may not be just NVDA’s stock price — but our entire understanding of mega-cap growth.

OMG 😮 These Nepal flood videos are absolutely horrifying‼️ The death toll has now risen to over 160 people. Hundreds are still missing and feared dead. Including hundreds of tourists. At least 54 Americans are amongst the people who have been reported missing thus far.

BREAKING: 𝕏 has published the latest update to the open-source algorithm powering the For You feed. The new update changes 47 files, adding 5,850 lines and removing 586. Key changes: • Phoenix now uses a long-dwell setting instead of short dwell, placing more emphasis on time spent viewing posts • The ranking weight for opening a video rises from 0.05 to 0.07, while dwell rises from 0 to 0.05 • New indexes help retrieve immersive videos receiving likes across different age ranges, extending up to 30 days • The Following feed gets stronger block and mute protection, including quotes and reposts involving blocked accounts or accounts that blocked the viewer • Cold-start ranking now uses views received specifically on Home instead of total views. Its Top-K setting drops from 5 to 2 • The follower threshold separating reply-spam detection from special reply ranking moves from 100,000 to 120,000 • Abuse models can now request approved actions such as labels, suspensions and account challenges, protected by allowlists, logging and a 16-action safety cap • The existing Brazil 2026 election-filter list expands from 665 to 2,328 account IDs. Posts remain eligible for people explicitly following those accounts • X’s newer ad brand-safety check is now enabled by default • A new priority-post stream has been added to the early content-quality screening system 𝕏 is not just talking about algorithmic transparency. It is publishing the code. The most transparent platform on the internet.

We’re back in Singapore 🇸🇬 News is bringing the Live News Desk to TOKEN2049 Singapore for year two. 🗓️ Oct 7–8 | Marina Bay Sands 🎙️ Live interviews + floor coverage Grab tickets before prices rise in September: BITCOINCOM10 |