7D Top Tokens on Everything (July 3, 2026) 1. $BTC- $61,280 (+4.2%) 2. $ETH - $1,701 (+11.2%) 3. $SOL - $80.37 (+20.3%) 4. $ZEC - $426.77 (+4.5%) 5. $HYPE - $66.40 (+7.1%) 6. $E - $0.3350 (+0%) Make your move on the app.

Foreign born population of each country : Jan 2001 Jan 2025 🇦🇹 8.7% 22.5% 🇧🇪 8.4% 20.2% 🇩🇰 4.8% 14.4% 🇫🇷 5.5% 14.0% 🇩🇪 8.9% 20.5% 🇬🇷 6.9% 11.0% 🇮🇸 3.1% 21.8% 🇮🇪 4.0% 23.3% 🇱🇺 37.5% 51.5% 🇳🇱 4.1% 16.8% 🇳🇴 4.1% 18.7% 🇸🇮 2.1% 15.5% 🇪🇸 3.4% 19.3% 🇸🇪 5.3% 20.8% 🇬🇧 4.3% 20.0% Now add children born to foreign parents and the situation looks even worse. We are living through the demographic annihilation of the people of Europe.

The models people choose. Past 7 days on Anuma: 1. grok-4.5 @xai 25.9% 2. claude-sonnet-5 @AnthropicAI 20.7% 3. gpt-5.6-luna @OpenAI 19.5% 4. claude-fable-5 @AnthropicAI 8.3% 5. kimi-k3 @Kimi_Moonshot 5.9% 6. kimi-k2.7-code @Kimi_Moonshot 3.4% One memory. Every model.

Grok 4.7 is here. @SpaceXAI’s latest release brings stronger coding, longer-running agents and better knowledge work, at the same price and speed as Grok 4.6. The biggest improvements: • A larger base model, trained with longer reinforcement learning on harder tasks that can take hours to complete. • Better self-checking and handling of long context. • Improved document and presentation creation. • Native understanding of the Grok Bot harness for better conversations and general knowledge work. • A rebuilt safeguard system with stronger jailbreak resistance and fewer unnecessary refusals for legitimate cybersecurity work. The published benchmarks show meaningful gains over 4.6: • CursorBench 4.0: 40.4% → 46.3% • Terminal-Bench 4.0: 20.3% → 38.0% • EEBench: 53.0% → 64.0% • Harvey Legal Agent Benchmark: 15.8% → 19.6% • GDPval: 1,605 → 1,695 Elo Against competitors, Grok 4.7 beats GPT-5.6 Sol on CursorBench and Terminal-Bench, and leads both Sol and Fable 5.1 on EEBench and Harvey. Fable still leads on CursorBench, Terminal-Bench and GDPval. Strong progress, with a particularly compelling price-performance story. Pricing starts at $2 per million input tokens and $6 per million output tokens. A fast variant offers twice the output speed at twice the price. Available now in Cursor, Grok Build and the API.

During Tesla Cybercab launch week in Austin, I took a total of 12 paid Cybercab rides and kept every receipt. TOTAL: • 12 rides • 29.7 miles traveled • $108.34 total spent • $3.65 average cost per mile • 2 hours and 19 minutes riding around Austin in a Cybercab • Compared to Uber and Waymo, every Cybercab ride was still ~30-50% cheaper EACH OF MY CYBERCAB RIDES: 1/ Sept 3 — 7:23 PM 3.9 miles · 16 min · $8.70 ≈ $2.23/mile 2/ Sept 3 — 7:53 PM 0.5 miles · 6 min · $4.65 ≈ $9.30/mile 3/ Sept 4 — 6:52 AM 2.5 miles · 12 min · $6.99 ≈ $2.80/mile 4/ Sept. 4 — 7:13 AM 2.4 miles · 11 min · $6.84 ≈ $2.85/mile 5/ Sept. 4 — 7:39 AM 1.8 miles · 11 min · $6.16 ≈ $3.42/mile 6/ Sept. 4 — 8:03 AM 1.4 miles · 8 min · $5.69 ≈ $4.06/mile 7/ Sept. 4 — 8:20 AM 3.3 miles · 15 min · $7.90 ≈ $2.39/mile 8/ Sept. 4 — 10:58 AM 4.0 miles · 19 min · $8.78 ≈ $2.20/mile 9/ Sept. 4 — 11:58 AM 2.6 miles · 8 min · $7.08 ≈ $2.72/mile 10/ Sept. 4 — 2:17 PM 2.8 miles · 11 min · $13.71 ≈ $4.90/mile 11/ Sept. 5 — 12:57 PM 2.4 miles · 10 min · $16.18 ≈ $6.74/mile 12/ Sept. 5 — 1:36 PM 2.1 miles · 12 min · $15.66 ≈ $7.46/mile One of the biggest things I learned from actually using Cybercab is that you cannot judge the economics from just one ride. Pricing is dynamic. Some of my longer rides came in cheaper around $2.20–$2.40 per mile. Some of the shorter or higher-demand rides were much more expensive. Sometimes, the Cybercab was even more expensive than the Model Y (Unsupervised) bc the demand was so high. Some of the rides also became more expensive as Cybercabs became bookable on September 4 to the general public. However, it’s hard for me to look at these receipts and not wonder how Uber and Lyft can compete if Tesla can scale Cybercab the way it wants to. Uber and Lyft were built around connecting riders with human drivers. That means every ride has to support a much bigger cost stack... like 1/ A human has to be paid. 2/ That person needs a car. 3/ That car has to be financed or purchased. 4/ It needs insurance. 5/ Maintenance. 6/ Fuel or charging. 7/ And then Uber or Lyft still needs its cut. Cybercab attacks the biggest cost in that entire system which is the driver... there is no driver waiting to be paid at the end of the ride. And Tesla is supplying the software. Tesla can build the car. Build the battery. Build the autonomy system. Operate the network. Control the app. Control the charging. And the team designed the Cybercab from Day 1 around being a Robotaxi instead of taking a normal consumer car and trying to make the economics work. This is a big deal. Bc if Tesla can manufacture these at huge scale, keep them on the road for most of the day, and keep bringing the cost per mile down, then Uber and Lyft are going to be competing with the company that built the vehicle, the driver, and the network ALL AT ONCE. And this was during launch week... with just ~45 Cybercabs, before this vehicle is anywhere close to mature scale. If Tesla can push that cost down further as the fleet grows to thousands and millions, while Uber and Lyft still have to pay a human being to sit behind the wheel… I really don't see how these companies can survive... I think the days of Uber and Lyft are limited.

These systems were built for humans reading charts. Now AI agents are starting to act on the data itself. At HLTH, Brad Genereaux, Global Lead for Healthcare Alliances at NVIDIA, and Susan Mullaney, Chief Operating Officer at Blue Shield of California, join ICONIQ's Caroline Xie to explore what AI-ready data infrastructure requires when the end user is a system making decisions at scale. 📅 Tuesday, November 17, 3:20-4:00pm 🎙️ "Reimagining Interoperability for the Agentic Era" 📍 Ferrari Stage Register now: Disclaimer:

🚨 Grok 4.7 is out. The biggest jump here: Terminal-Bench goes from 20.3% to 38%. It also beats GPT-5.6 Sol on CursorBench: 46.3% vs 41.7%. Same token pricing as Grok 4.6. Still behind Fable 5.1 on both, but this is a solid jump.

10 years ago: 30-yr mortgage rate was 3.4% & median existing home price in the US was $240k Today: 30-yr mortgage rate is 6.8% & median existing home price is $429k Result: $38k increase in down payment (assume 20% down) & 163% increase in monthly payment (from $851 to $2,237) Video:

10 years ago: 30-yr mortgage rate was 3.4% & median existing home price in the US was $243k Today: 30-yr mortgage rate is 6.7% & median existing home price is $434k Result: $38k increase in down payment (assume 20% down) & 160% increase in monthly payment (from $862 to $2,240) Video:

WEMBY IN HIS FIRST 10 POSTSEASON GAMES: 👽 20.3 PPG 👽 10.7 RPG 👽 4.1 BPG Spurs win Game 6 on the road and advance to the Western Conference Finals for the first time since 2017!