RootData Tokenized Assets Data: Binance and Bitget Rank Top 2 by TradFi Asset Depth According to RootData's latest tokenized assets dashboard, Binance and Bitget lead in TradFi asset depth. 🔸Binance: ~$152M | Rank #1# | Market share 33.6% 🔸Bitget: ~$138M | Rank #2# | Market share 30.6% These two exchanges account for approximately 64.2% of total TradFi market depth, holding more than 60% of the share. "The TradFi asset data covers crypto native products such as contracts and tokenized assets, and does not include traditional stock broker data."

See here for battery installation size - 69.0 kWh per NEV (up 27.9% YoY). 64.2 for BEV & 41.2 for PHEV pax vehicles, remaining growth down to much higher trucking electrification) Avg truck 217 kWh, coach 213.4 kWh, PV 56.5 kWh so far in 2026. System wide battery Density has shifted w/ center around 140-160 Wh/kg Again, the big factor is actually not the energy density change but higher charge/discharge speed + lower cost.

Minneapolis Public Schools spent $25k per student this past year. Results? Black students: > Science: 95.2% are NOT proficient > Reading: 83% are NOT proficient > Math: 89.1% are NOT proficient Overall students: > Science: 77.2% are NOT proficient > Reading: 59% are NOT proficient > Math: 64.2% are NOT proficient

24H Top 5 Gainers on #KuCoin# (June 16, 2026) 1. $XTER - $0.01 (+63.64%) 2. $JTO - $0.78 (+43.04%) 3. $DN - $0.69 (+41.34%) 4. $SIREN - $0.16 (+39.56%) 5. $NOBODY - $0.00568 (+36.96%) Check Out and Sign Up on KuCoin! #Ku24hour# X, 8 AM HKT

This Yale + University of Chicago paper shows that real gap between LLM generated research ideas vs humans is not idea quality, but idea range: LLMs think narrower than human researchers. The researchers built a controlled test from 11,683 real papers, using each paper’s nearby prior work as the shared starting point. They asked models to propose a new motivation and method from those same prior papers, then compared those ideas with the real human paper ideas. Instead of asking whether 1 idea looked novel, they labeled each idea by what gap it noticed and what kind of contribution it made. Human ideas spread across many patterns, such as explaining mechanisms, testing failures, measuring evidence, building systems, and improving efficiency. Only 12.1% of human ideas were mainly about connecting separate work, but 47.1% to 64.2% of LLM ideas did that, meaning models used this move about 4 to 5 times more often. Even extra reasoning made this pattern stronger, suggesting models often polish a familiar recipe instead of finding more varied research moves. --- – arxiv. org/abs/2607.01233 Title: "Measuring the Gap Between Human and LLM Research Ideas"

🏆 River4FUN Top 10 Creators 🥇 @CryptoUKong — 2.81% 🥈 @Franciscrypt1 — 2.77% 🥉 @RMac_5 — 2.70% 4️⃣ @crico41 — 2.64% 5️⃣ @LUCUIS_HQ — 2.61% 6️⃣ @hanhanbtc — 2.55% 7️⃣ @revolut20 — 2.53% 8️⃣ @evrendag1284 — 2.46% 9️⃣ @TheMrX — 2.34% 🔟 @shakibmunsi0 — 2.29%

KBDL and KORH set new daily rainfall records today. 🌧️ KBDL: 2.33" (previous record: 1.32") 🌧️ KORH: 2.64" (previous record: 1.82") With several hours still left in the day, these totals will increase. A final record report will be issued overnight. #CTwx# #MAwx#