> OpenAI slashed GPT 5.6 Luna by 80% > Anthropic launched Opus 5 at half the price of Fable 5 > cancelled a planned Sonnet 5 price hike.... did you see the pattern? OpenAI and Anthropic are cutting prices by ~25% since mid July do Chinese models are forcing their hand? cheap models loke DeepSeek, Kimi, Qwen are no longer just good enough... they are starting to hurt the big players where it matters

🚨 OPUS 5.5 Leaks > Anthropic is stealth testing "claude-opus-5-5" > Internal codename "claude-wafer-eap" > Previously expected as Opus 5.2, but plans reportedly changed > It's way better than current Astra + Fable 5.1 > ~20% cheaper than Opus 5.1 > $4 input / $20 output per 1M tokens > Context window reportedly around 900k - 1m Is anthropic actually back again?

> what token deal did you take? > i took no deal, i turnt it down > oh.. > ye, i turnt it down just to do this.. just to grind from the trenches > so you had an opportunity to take deals? > ye, with stables and everything > what token? > i think it was like.. a raydium token? a big token on raydium.. was a big token tho. and they offered me like.. 15.. some shit like that.. 10%? something like that.. 5%? something like that > wait wait wait > ha.. supply deal > ok but not 5%. they offered you 5% to call a token? > ye > the fuck you doing here? > like.. what.. like you know what i'm saying.. but i was so younger like > wait wait wait.. are you sure they offered you 5% > sheee... i turned it down > it was a deal like i had to push this token for like this decade > but you would get 5%? > it was in the high %s though

Foreign-born population, 1990 vs 2026: 🇬🇧 UK: 5% —> 17% 🇺🇸 US: 8% —> 15% 🇮🇹 Italy: 3% —> 11% 🇪🇸 Spain: 2% —> 20% 🇦🇹 Austria: 9% —> 25% 🇧🇪 Belgium: 9% —> 20% 🇩🇰 Denmark: 5% —> 14% 🇩🇪 Germany: 9% —> 20% 🇬🇷 Greece: 6% —> 14% 🇮🇸 Iceland: 3% —> 25% 🇮🇪 Ireland: 6% —> 22% 🇫🇮 Finland: 1% —> 10% 🇫🇷 France: 9% —> 14% 🇳🇴 Norway: 4% —> 18% 🇸🇪 Sweden: 9% —> 22% 🇨🇦 Canada: 15% —> 22%

Open weights models really accelerated! > Qwen-3.8 (2.4T), “second only to Fable 5” > Kimi-K3 (2.8T), “only behind Claude Fable 5 Max and GPT-5.6 Sol Max” > GLM-5.2 (753B): remarkably efficient and capable. The demand we’re seeing from Databricks customers is wild. This is super exciting.

happy launch week it's last week of september and it’s gonna be big one too as we’re expecting alot: > sonnet 5.5 > new openai model > agent "o" > minimax m3.1 > qwen 4 family sonnet 5.5 is expected to release today and it's huge step up from current model openai dev day is tomorrow too, so we’re gonna have alot more stuff from them which one are you most excited for?

coordination is the next big hurdle to getting 10x more output from agents it will be similar to how a ceo's role changes as her team grows from 5->50 instead of building directly, we'll develop systems that coordinate entire teams: communication channels, verification loops, etc. we'll give feedback and steer the system from above, ensuring that our vision is executed faithfully tomorrow's tools will help everyone do this!

# Neo4j Features and Practical Usage 🕸️ "If this server goes down, what chain of things stops with it?" Cypher's variable-length patterns answer that by traversing relationships across any number of hops. 🏷️ Title: Variable-length patterns (`*1..5`) / SHORTEST / Quantified Path Patterns 🔗 URL: 📘 Overview Variable-length patterns let you express paths whose hop count is not fixed, all in a single declarative pattern. Questions like "trace suppliers up to 5 levels deep" or "find one shortest path" become natural one-liners. Shortest-path finding and Quantified Path Patterns (QPP) belong to the same family. ⚙️ How It Works ・Quantified relationships (legacy syntax): `[:REL*1..5]` matches 1 to 5 repetitions. `*2` is exactly 2, `*3..` is 3 or more, `*..10` is up to 10, `+` is one or more, and `*` is zero or more. ・Quantified Path Patterns (QPP): wrap a whole pattern in parentheses and quantify it, e.g. `((a)-[r:NEXT]->(b)){1,3}`. It is GQL-conformant and supports inline `WHERE` predicates inside the repetition. ・Group variables: variables declared inside a QPP become lists when referenced outside (e.g. `r` becomes an array of relationships). Combine with `reduce()` to compute, say, total distance along a path. ・Shortest paths: `SHORTEST k` returns k shortest paths, `ALL SHORTEST` returns every tied-shortest path, and `ANY` returns any one. The legacy `shortestPath()` / `allShortestPaths()` functions still work but the keyword syntax is faster. 🛠️ Practical Usage Trace a part's suppliers up to 5 levels deep: ```cypher MATCH (p:Part {sku: $sku})-[:SUPPLIED_BY*1..5]->(supplier:Company) RETURN DISTINCT ``` Find the single shortest introduction chain between two people: ```cypher MATCH path = SHORTEST 1 (a:Person {id:$a})-[:KNOWS]-+(b:Person {id:$b}) RETURN [n IN nodes(path) | AS intro_chain ``` 💡 Use Cases ・Impact analysis: how far a server failure cascades. ・Money-laundering detection: tracing fund-movement paths between accounts. ・Org charts and social graphs: boss-of-boss lookups, friend-of-friend shortest reach. ⚠️ Caveats ・Unbounded `*` or `[:REL*]` causes path explosion and can stall on millions of matches. Always set an upper bound such as `*1..5`. ・Pruning early with labels, relationship types, and inline predicates makes queries dramatically faster. QPP is built for this kind of pruning. ・By default Cypher does not allow re-traversing the same relationship; be aware that this behavior can be modified. #Neo4j# #Cypher#

relax AI won’t take your job, it’ll just take your weekends your sleep your hairline and eventually your pulse. let me explain with a wall street love story: > you’re a 1976 Wall Street trader > pen and index cards, screams orders into a phone pit > handles 1 sector. goes home at 5 > 1985, you get a computer, real time quotes, electronic execution > now handles 3 sectors. goes home at 8 > 1999 you get the internet, scans global markets from your desk > now covers 5 sectors. goes home at 10 > 2026, you get AI, does the research of a whole analyst team solo > now does the work of 10 people. doesn’t go home > you’re now the most productive trader who ever lived > you die at 43 > but hey at least you were productive > they’ll replace you when you’re dead though so don’t worry about that part

do you understand what the New York Knicks just did to 53 years of suffering... every fan who lived through this knows the number. 1973. Willis Reed. The limp. That's the last time this franchise won anything. Since then: 15 coaches, 4 rebuilds, the Isiah Thomas era, the James Dolan era, the lottery picks that never worked, the trades that always failed, the Garden that became a punchline. 53 years and last night it ended in San Antonio, 94-91, Game 5 > 53 years - that's longer than most NBA players have been alive. the entire city of New York waited a lifetime for this > Knicks won 15 of their last 16 playoff games - the most dominant postseason run in franchise history > 11 consecutive playoff wins all by double digits - highest scoring margin +262 points of any postseason team in NBA history > defeated Victor Wembanyama and the Spurs 4-1 - the kid who was supposed to be the next dynasty, gone in 5 > Jalen Brunson. Karl-Anthony Towns. built through patience, not superteam shortcuts > Donald Trump personally congratulated Jim Dolan on social media. even the president felt this one Think about the fan who was 25 in 1973 watching Willis Reed walk out of that tunnel. They're 78 now. they watched Game 5 last night. That's who this championship is really for. Every city has a curse. New York just buried theirs.