5/
And then it flags harmless biology questions like “do bumblebees fart?”

That is not protecting humanity.

That is a classifier with a concussion.

If your flagship model treats basic curiosity like a biosecurity incident, the product is broken.

7/
This is the real problem with Fable 5.

Maybe the raw intelligence is there. Maybe it’s amazing under the hood.

But if users constantly hit fallbacks, limits, account holds, and dumb refusals, then the practical product is useless.

Anthropic didn’t release a frontier model.

They released fear with a chat box.

Palo Alto Networks CEO Nikesh Arora said 90% of enterprise workers are behind on AI, and it could determine the fate of their careers.

He expects 20% to 25% of his workforce to change within 12 months.

According to a 2025 Orgvue study, 39% of leaders had already cut workers after deploying AI.

OpenAI has proposed giving Washington 5% of its $852B business to ease AI pressure.

The idea borrows from Alaska’s oil fund, which shares resource wealth with residents.

Here, the resource is not oil, but future income from advanced AI systems.

OpenAI also wants other major AI companies to give similar 5% stakes.

Anthropic, Google, Meta, and others have not agreed to join this plan.

No deal exists yet. The mechanism would likely be: OpenAI gives shares to a government-linked fund, that fund holds them, and future IPO gains or dividends support public payouts.

The hard part is legality. The legal route is unclear, and a deal may need Congress, especially if the government creates a formal public fund.

The Intel deal made this idea less theoretical after taxpayers received a 9.9% stake.

OpenAI has already proposed a public wealth fund giving citizens AI-linked financial upside.

Shareholders matter a lot here. OpenAI Foundation owns 26%, Microsoft owns about 27%, and employees plus other investors own 47%.

A new 5% stake could dilute everyone unless the shares come from an existing holder.

So OpenAI’s board, Foundation, Microsoft, major investors, and maybe regulators would need to accept the structure.

The cleanest path would be non-voting shares placed in a public wealth fund, so the government gets upside but not control.

The messiest path would be voting shares, because then Washington becomes both regulator and part-owner.

Fable 5 is officially back online, and you're probably wondering how to use it without going broke.

Here's the advice from Anthropic engineers, and the exact system I've personally come up with to cut token costs by 50%+:

The 10-80-10 System - Biggest difference:

→ First 10% (Planning): Use Fable to define the structure, approach, success criteria, and constraints. Think of it as your architect. Get the plan right before anything else.

→ Middle 80% (Execution): Switch to a cheaper model. Opus 4.8 for standard work, Haiku for light tasks.

Pro tip here: Ask Fable to fan out subagents for/loops.

→ Final 10% (Review): Bring Fable back in to check the output against the original plan. Because it reviews a finished result rather than generating from scratch, it uses a fraction of the tokens.

4 smaller tips that also make a difference:

• Start on medium effort, not max - Fable on medium beats Opus on extra high.

• Delete old skills and instructions. Prompts built for earlier models perform worse and cost more in Fable. Anthropic recommends starting fresh.

• Give Fable the "why" behind every request. It gets things right the first time more often. Fewer iterations = fewer tokens burned.

• Run /usage regularly. Once Fable moves to pay-per-token on July 7th, this becomes essential.

Two expensive mistakes to avoid:

• Fable is now the default model when you open Claude Code. Check the model selector before every session.

• Set a hard monthly spend cap before July 7th. Settings → Usage → Adjust Limit. Fable burns fast on autonomous runs.

The model is worth every token when used right, but you can quickly rack up token costs. Be sure to save and implement these tips.

The initial production ramp for Tesla’s Optimus robot will be very slow.

During the Q1 2026 earnings call, Elon Musk confirmed the “production S curve will be very slow in the beginning.”

Optimus is an entirely new product category, so Tesla is building brand-new manufacturing processes and technologies very different from vehicle production.

The company is currently setting up its first-generation lines at the Fremont factory to master this process.

But while the start will be gradual, the long-term ambition is massive.

Fremont is being designed for 1 million robots per year, and a second-generation line at Gigafactory Texas is targeted to start production around summer 2027 with the ultimate goal of scaling to 10 million robots annually.

Slow at first. Exponential later. Classic Tesla S-curve.

💰 Current GB10 market - DGX Spark, Ascent GX10,Veriton GN100, Edge Xpert🧠💸 Prices going up.

I review current retail prices for 60 GB10 listings across 6 retailers.

🔹 1TB systems: ~$3,989–$4,000
🔹 2TB systems: ~$4,400–$4,617
🔹 4TB systems: ~$4,500–$5,000
🔹 2-pack bundles: ~$9,449–$10,800

Verdict: GB10 is still buyable, but prices are rising and are currently around $4K–$5K for most home AI buyers.

A reminder that the entire original Fable 5 system prompt was leaked.

This is the behavior that the original Fable carried:

github.com/elder-plinius/CL4R1T4S/blob/main/ANTHROPIC/CLAUDE-FABLE-5.md

Netflix and the other streamers need to wake up.

They should be building Seedance 2.5-level video models directly into their platforms, or creating their own version, and let indie creators make short films, weird experiments, mini-series and actually profit from them.

Because the long-term threat isn’t just YouTube or TikTok. It’s creative people with AI tools suddenly making better, weirder, faster entertainment than the corporate machine.

My bet: within 5 to 10 years, a huge chunk of what people watch will either be indie AI-made content or stuff they generated themselves.

Streamers can either own that future, or get eaten by it.

One of the weirdest things right now is how few normal people actually use AI properly.

Most still treat it like a slightly smarter Google. Ask question, get answer, move on.

Meanwhile tools like Codex and Claude Code are already agentic enough to automate huge chunks of actual work. Not “help me think of ideas,” but “go through this repo, fix the bug, write the tests, update the docs, explain what changed.”

That’s not search. That’s delegation.

The AI gap isn’t really between people who have access and people who don’t. It’s between people who still prompt like it’s 2022 and people who understand they now have junior agents working for them.

The global economy is on the verge of a massive transformation, driven by humanoid robotics.

According to major financial institutions, the market potential is staggering.

Here is what the data shows

$5 Trillion Market: Projected value by 2050

Cost Efficiency: Robot unit costs dropped >40% from 2022–2024

Mass Adoption: 3 Billion units projected globally by 2060

THE TEMPERATURE LADDER STRATEGY THAT TURNS POLYMARKET WEATHER INTO ASYMMETRIC EDGE (LADDER EDGE STRATEGY)

Most traders pick one most likely temperature bucket and hope it prints

Ladder traders do something smarter: they spread small money across 3–4 adjacent buckets so that whichever one resolves pays the whole stack

This turns weather markets into a positive-skew game where one correct bucket more than covers the cost of the losing ones

[why ladders work so well on short-horizon markets]

Models give a point forecast that falls into one bucket

But that point is often off by 1–3°C, sending the real temperature into a neighboring bucket

Buying the whole cluster cheap (ladder usually costs under $1) means you don’t need to guess the exact number

You just need the actual temperature to land in one of your buckets

[how to build a strong ladder in practice]

Example for Singapore (cluster 29–31°C):

- 29°C @ 0.2¢
- 30°C @ 15¢
- 31°C @ 35¢

Total: ~$0.50. One winning bucket at 100¢ makes the position profitable

[when this edge shines brightest]

- Transitional days when models disagree
- 24–48 hour horizon (D+1 and D+2)
- Volatile cities like Singapore, Miami, Tokyo, Shanghai
- Right after a fresh model run before the market reprices

Add an underdispersion filter (ensemble spread tighter than historical) and the win probability rises noticeably

Ladder + basic ensemble check is one of the cleanest asymmetric plays on Polymarket right now

Save this post!

Kelly vs Flat Sizing in Polymarket Weather - Who’s Winning in 2026

One of the most important (and rarely discussed) questions that separates profitable traders from everyone else

>Kelly Sizing (Aggressive Approach)

Position size is calculated based on your edge using the Kelly formula

Examples:

- ColdMath often uses a Kelly variation - aggressively increases size on strong signals in secondary cities.
- Some Asian snipers (like opopv) go very large on ultra-cheap buckets with high conviction

It is recommended to use the fractional Kelly criterion to reduce risks

>Flat Sizing (Conservative Approach)

Fixed percentage of bankroll per trade (usually 0.5–2%)

Examples:

- VibeTrader sticks to more consistent sizing and builds ladders across multiple buckets
- Many stable bot traders use flat sizing to avoid big drawdowns during losing streaks

>What the current market shows:

Kelly traders win during periods with strong mispricings (higher PnL volatility but bigger upside)

Flat traders perform better in sideways markets and when edge is weaker (smoother equity curve)

>Parity Terminal lets you see this in real time:

- Actual sizing of every top trader on each market
- How Kelly and flat traders behave on the same cities
- Who handled recent drawdowns better
- Real PnL comparison between different risk management styles

You’re not just copying trades - you’re copying the risk management systems of strong players

Most traders pick one method and never change it.
Consistent winners adjust sizing to the current market, their psychology, and bankroll size

Start tracking not just the traders, but how they manage risk 👇

predictparity.com

GTA 6 will probably be the last GTA where NPCs are still mostly scripted background noise.

GTA 7 is going to be a different beast.

Imagine NPCs that feel like actual people. They remember you. They have routines, histories, grudges, friendships, jobs, secrets, bad days, weird habits. You don’t just “talk” to them through dialogue trees, you actually interact with them like they’re living inside that world.

And the story won’t just be a fixed rollercoaster anymore. There will probably still be a main framework, but everything around it will shape itself organically through your choices, your relationships and the chaos you create.

People are 100% going to fall in love with NPCs. Some NPCs will become someone’s best friend. Some random side character will accidentally become more memorable than the actual protagonist.

GTA 6 will be huge.

But GTA 7 might be the first game that feels alive.

Me after checking my portfolio.

When you know the trade is going to zero.

But you've mastered your emotions and accepted it.

Empty seats are better than wrong company