Arena

Tesla is hiring a Machine Learning Engineer for Realtime Games, Digital Optimus, in Palo Alto. The job: build agents that play AAA games, browse the web and use pro apps at superhuman levels. Why games? Digital Optimus, the Tesla and xAI project Musk announced in March, reads screen video and acts with a keyboard and mouse. AAA games are a safe, endless, real-time proving ground for exactly that, the same approach DeepMind's SIMA uses. Tesla's posting says it will benchmark how skills transfer across games, general computer use, FSD and Optimus. tesla.com/careers/search/job…

Quantum progress. Powered by collaboration. We're excited to announce we're launching a new co-design platform with @IBM and @ORNL's @QuantumSciCtr to advance quantum error correction. At its foundation: Umbra, an HPC system powered by AMD Instinct MI355X GPUs and 5th Gen AMD EPYC CPUs, working alongside IBM quantum computers. bit.ly/4yXwcHJ

Robotics AI is only as good as the real-world data behind it. That's what makes Maxinsights' latest progress interesting. → $30M seed funding led by Peak XV 
→ 2M+ hours of real-world work data delivered 
→ 50+ robotics and foundation model teams in the pipeline 
→ $250M projected annualized run rate for 2026 The race to build smarter robots is accelerating, and the data infrastructure behind it could become one of the biggest opportunities in AI.

Autonomous drone delivery startup Zipline raised $1.5B at a $21.5B valuation, up from $7.85B after raising $600M in January, and plans to grow US manufacturing (@kelly_cloonan / Wall Street Journal) (Visit Techmeme dot com for the link and full context!)

Wow! Agents are now creating 20,000+ PostgreSQL instances a day on Tencent Cloud. This is up 80x in a year! 14 million sandboxes are created daily. Agents run isolated environments in these sandboxes to execute code and browse the web. Tencent's office AI agent has received 9 billion (with a B) task requests in the last 8 months!

DAN IVES SAYS THE MIDTERM RESULTS WILL SLOW THE AI DATA CENTER BUILDOUT He now expects Big Tech's capex growth to peak in 2027, earlier than his previous 2028 to 2029 view. - 10% to 20% of the 800 to 1,000 planned US AI data centers could be scrapped or face long delays - Big Tech's stock and debt raising could be about 25% lower over the next year - Losers: neoclouds, power suppliers, and some chip and memory companies - Winners: Apple $AAPL, Meta $META, Microsoft $MSFT, Google $GOOGL, Amazon $AMZN, Palantir $PLTR, Snowflake $SNOW, CrowdStrike $CRWD, Palo Alto Networks $PANW, Nvidia $NVDA He says his overall bullish AI view hasn't changed. He's just more selective.

The Federal Energy Regulatory Commission (“FERC”) has authorized our acquisition of Long Ridge Energy & Power. Closing is expected in the coming weeks. The deal will add 1,600+ contiguous acres and a power plant currently authorized to sell 485 MW, expected to reach 505 MW nameplate in 1H 2027. Learn more: ir.mara.com/news-events/pres…

$APP Q3 2026 Earnings — Double Beat AppLovin delivered a strong Q3 beat on November 4, 2026:⁠ Revenue: $2.185B (+55% YoY) vs. ~$2.07B consensus Diluted EPS: $4.30 vs. ~$4.03 estimate Net Income: $1.44B (+72% YoY) | 66% net margin Adjusted EBITDA: $1.84B (+59% YoY) | 84% margin Free Cash Flow: $1.4B

‼️ Revolut says it cut AI coding costs about 10x by making a self-hosted Chinese model its default in place of Claude Code. It runs Z ai's GLM on its own Nvidia GPUs for about $0.30 per million tokens.

SHIFT4 $FOUR JUST REPORTED Q3 EARNINGS - Revenue: $1.32B, missing expectations of $1.33B 🔴 - Adj EPS: $1.49, beating expectations of $1.37 🟢 - Gross Revenue Less Network Fees: $648M (+10% YoY) - Adjusted EBITDA: $310M (+6% YoY) - Adjusted EBITDA Margin: 48% Cuts FY26 Guidance: - Non-GAAP EPS: $5.05-$5.15, below expectations of $5.17 🔴 - Gross Revenue Less Network Fees: $2.45B-$2.46B - Adjusted EBITDA: $1.11B-$1.13B Key Updates: - Shift4 One: Live in 15 countries (nearly $50M Global Blue synergies expected) - Share Repurchases: 4.2mm shares for $190mm ($10M preferred shares)

About 600,000 Nvidia H200 AI Chips Are In Hong Kong Awaiting Shipment To Mainland China – RTRS Cites Sources - China Has Yet To Approve Large-Quantity Imports Of Nvidia H200 Chips, Though Smaller Volumes Have Entered Through Unofficial Channels - Major Chinese Internet Companies Have Each Received About 10,000 Nvidia H200 Chips In Recent Months

Agility Robotics is officially heading to Nasdaq. The company has completed its SPAC merger and is expected to begin trading today under $AGLT. The company reports over 65,000 hours of real-world robot operation and more than $300M in committed multiyear Digit orders. robotico.market/news/agility…

UNITY SOFTWARE $U JUST REPORTED EARNINGS EPS of $0.25 beating expectations of $0.05 🟢 Revenue of $622M beating expectations of $567M 🟢 $U's first move following its earnings is up by more than 20%

Voters backed data-center limits in 40 of 41 local votes Tuesday. Today OpenAI pledged to pay full power costs at campuses it owns, publish construction plans, and drop NDAs with officials. Building AI now faces a local veto. Covering the bill is the answer.

$LMND posting strong growth again this quarter, and a 64% net loss ratio. I’d say the AI is working. Affirmed positive Adj EBITDA guidance for Q4, which is a huge milestone. I’ll keep digging but this looks very solid.

MICRON $MU PAUSES CONSTRUCTION OF UP TO $4.5 BILLION MEMORY CHIP PLANT IN TAIWAN AMID LABOR DISPUTE. The Taoyuan facility was expected to begin producing DRAM and HBM chips in 2028. Workers are demanding higher compensation, including a proposal to distribute 15% of Micron's operating profits to employees globally. Micron says existing Taiwan operations continue as normal. The island accounts for roughly 60% of the company's global DRAM production.

ACM Research, $ACMR, Q3-26. Sales crushed estimates and guidance jumped. An investment loss hit GAAP earnings. 🟢 Revenue: $367.7M vs. $310.6M est. 🟢 Adj. EPS: $0.55 vs. $0.51 est. 📈 FY26 guide: $1.24B–$1.28B (raised) ⚠️ GAAP EPS: $0.02; $39.1M unrealized loss

ERNIE 5.5 Flash Base is now open source — a 280B-parameter model with 14B active per token, and it already matches SOTA at its size! And this is just the start — the full ERNIE 5.5 Flash is on its way. 👀

Hy4 from Tencent scores 35 on the Artificial Analysis Intelligence Index v5 and is the #2 model from a China-based AI lab Hy4 is the latest model from @TencentHunyuan and is the successor to Hy3 released earlier this year. It scores 35 on the Artificial Analysis Intelligence Index v5, equal with Grok 4.7 (xhigh) and 1 point behind Claude Haiku 5.5 (max). Hy4 is the #2 model from a China-based AI lab, behind only Kimi K3.1 Pro, which scores 46. Hy4 is priced at $0.834/$2.501 per 1M input/output tokens. Key takeaways: ➤ Hy4 excels at agentic coding tasks. Hy4 scores 31% on FrontierCode 2.0, compared to 32% for Claude Fable 5.1 (max). It is the leading model from a China-based AI lab, with DeepSeek V4.1 Flash 1017 (max) scoring 28% and Kimi K3.1 Pro scoring 25%. On Terminal-Bench 4.0, it scores 37%, the fourth-highest score among models from China-based AI labs ➤ Hy4 outperforms its peers on knowledge and reasoning. Hy4 achieves accuracy of 50% on AA-Omniscience v1.1, 1 point ahead of Kimi K3.1 Pro, but has a high hallucination rate of 89% compared to Kimi K3.1 Pro’s 37%. On HLE-Diamond, it scores 33% compared to Kimi K3.1 Pro’s 37% ➤ Hy4 offers a competitive Capability vs. Cost trade-off compared to to peers. With a Cost per Intelligence Index Task of $0.78, Hy4 (35) is 10-times cheaper than Grok 4.7 (xhigh, 35) and 13-times cheaper than Qwen3.8 Max (0902) (34) but almost twice as expensive as Claude Haiku 5.5 (max, 36) Other model details: ➤ Context window: 1 million tokens ➤ Pricing: $0.834/$2.501 per 1M input/output tokens. Cache reads $0.042 per 1M tokens ➤ Multimodality: Text and image input, with text output

AI is using more and more of the world’s energy. But how much economic value are we getting from AI? We’re introducing Joules-to-GDP (J2G), a framework that measures how well AI turns energy into economic value and shows which tasks, models, and hardware give the best return. Across 44 occupations in finance, engineering, law, administrative work, and more in @OpenAI's GDPval, we arrive at three findings: 1) The tasks with the highest economic value are not the tasks with the highest economic value per joule. For example, CAD design earns ~10% more per task than building websites, but the latter earns ~27% more value per joule. 2) The most powerful model isn’t always the best use of energy. Gemma 4 31B delivers 56% of GLM 5.2’s net value with 23% of the energy, for 2.5x the value per joule. 3) More chips don’t guarantee proportionate returns. Moving the same model from 1 to 8 NVIDIA H100s uses 3.2x the energy but cuts completion time by only 22%, with about the same value. With @SnorkelAI, we’re also releasing GDPWorks, a benchmark for economically valuable tasks across 36 additional occupations. Joint work co-led by @amirzeinaalii and @Avanika15, with @Mersad_Abbasi, @Jon_Hartley_, John Hennessy, @HazyResearch, and @Azaliamirh. More details below 🧵

OpenAI’s Greg Brockman reveals an unannounced JPMorgan Chase deal, with the bank using Codex and OpenAI’s cyber models to secure itself “Well, so within the company, we were probably, I don’t know. Like, I think our enterprise revenue was about 30% versus consumer at 70%. And now we’re probably somewhere around, like, we’re majority enterprise. And it’s not that consumer has shrank. Right? It’s been growing, but it’s the enterprise segment has really taken off." "And so I don’t know exactly how to quantify in the broader market, but you can see the way that we’re winning deals. So for example, actually, one that’s hot off the press, has not been previously announced, is that we just papered a partnership with JPMorgan Chase, and that they’re going to be using Codex." "They’re going to be using our cyber models to secure themselves, deploying our models for enterprise transformation knowledge work across the company." "And that for me is like such an iconic institution in such an important domain. Right? A highly regulated enterprise that trust is, like, so key to what they do and that they chose us and that we’re here to be a great partner.”