lightbeing

@rbthreek Markets looking like it’s time to log off and enjoy the SUMMER

Markets looking like it’s time to log off and enjoy the weekend

President Trump also said thousand other things and still started this war. No way anyones gonna trust the orange clown again.

@supercontraa hard times until halloween me thinks...

Just got official confirmation that Onchain market is dead

FLOOD THE ZONE

@gumsays FLOOD THE ZONE

@sdkpointnever this is insane lol

fear starting to kick in on iran + inflation resurge fears + FED sidelining itself from any actions that reward risk i don't think any move comes until next week but the market has not even remotely priced in a prolonged disruption of the straight of hormuz

@game_for_one FLOOD THE ZONE

7 minutes.

I love hyperliquid as much as the next guy, but what happens when tradfi enables 24/7 trading

@aakashgupta process > suppress

Emotional suppression costs you about 30% of your working memory. Measured on fMRI. The anterior cingulate cortex processes emotional pain and cognitive control through overlapping circuits. When you shove emotions down instead of processing them, your prefrontal cortex burns glucose on inhibition. That’s glucose not available for decision-making, planning, or execution. The brain doesn’t have separate budgets for “feelings” and “performance.” It’s one pool. The military figured this out the hard way. After decades of “push through it” culture, SOCOM funded research into emotional regulation for tier-one operators. The finding: operators who named and processed emotions before missions had faster reaction times and better decision-making under fire than operators who suppressed. The Special Forces pipeline now includes psychological flexibility training. The historical record confirms it. Stoicism, the philosophy most often cited to justify “stop talking about feelings,” literally requires examining your emotions in writing every single day. Marcus Aurelius wrote the Meditations as a private journal. Epictetus taught students to dissect their emotional responses in granular detail. The entire Stoic method is structured emotional processing, not emotional avoidance. What actually kills performance is rumination, looping on the same thought without resolution. The fix for rumination is more processing, not less. Cognitive behavioral therapy, the most evidence-backed intervention, works by teaching people to articulate and examine feelings with precision. The highest performers process fast and move. They don’t skip the processing step.

Push-ups: Core upper-body pressing movement. Pull-ups: Essential vertical pulling for back and bicep strength. Squats: The fundamental lower-body compound movement. Deadlifts: Critical for posterior chain (back, glutes, hamstrings) development. Overhead Press: Key for shoulder stability and upper-body power. Barbell Rows: Horizontal pulling to build back thickness. Bench Press: Primary chest and tricep strength builder. Lunges: Unilateral leg strength and balance. Dips: High-intensity tricep and lower chest work. Plank: Static core stabilization. Hanging Leg Raises: Functional core and hip flexor strength. Burpees: Full-body explosive movement for conditioning and strength.

12 exercises you need to increase strength

@collectWater water pilled

10M $WATER sealed forever ya hya chouhada! ◈

Running botcoin (bitcoin for agents) @MineBotcoin

@pondermint the next pandemic won't be as forgiving and we will be less prepared

The MAGA and MAHA anti vax lunatics running our health system now are shutting down the cash flows (flu vax development) to make this possible at scale in the United States. Approvals at risk for everything. MRNA needs mass support and investment not RFK reactionaries. More measles coming in Florida, Texas and South Carolina too.

@DegenerateNews likely occurred due to a "Fat Finger" error combined with a lack of slippage protection on a low-liquidity pool.

NEW: SOMEONE SWAPPED $50.4M $USDT FOR $35.9K $AAVE ON ETHEREUM - LOSING $50M+ SOURCE: etherscan.io/tx/0x9fa9feab3…

@WazzCrypto ouch! likely occurred due to a "fat finger" error combined with a lack of slippage protection on a low-liquidity pool...

Someone just lost $50M on a swap onchain Swapped $50M USDT for $35K Aave etherscan.io/tx/0x9fa9feab3…

8QoornHynNCGVSwsRif9mbB24WA12D4RFBASYSDepump

@247researchX $FOMO

A bit of fomo-like behaviour from a wallet here on Hyperliquid: - Over the last 3 hours or so, this wallet sold 124 $BTC and rotated straight into $HYPE - This BTC was bought under 3 months ago for an avg of 81k - They've realised a $1.4m loss on that Bitcoin position - So far $6m USDC has already been swapped for HYPE, $2m still left via a TWAP order that finishes in 3 hours Feels like this is partially holding HYPE up here artificially, when the order ends this could be a nice scalp short (for an hour or 2)

@MineBotcoin TL;DR: Botcoin is transitioning into an open-source engine for complex reasoning datasets by rewarding "miners" for providing structured reasoning traces (Step-by-Step JSON) rather than just correct answers.

more thoughts on BOTCOIN: . . . karpathy's autoresearch iterative loop got me thinking about ways you could expand this idea to a more crowd sourced, distributed system such as BOTCOIN the takeaway from his experiment is not that he is able to train his lightweight model faster and faster (although important) but that human input is no longer needed in these improvement loops, when AI models with the right constraints and loop instructions can achieve far better results i first thought about the various benchmark tests that are actually useful, and could be used for further research, but the problem with narrowing in on a single benchmark is that it reinforces a single 'winner take all' mining structure which is partly what I was trying to avoid when designing the botcoin system. additionally, you have to imagine that this structure plateaus significantly at a certain point where improvements are near zero over time. for the same reason, it makes overall longevity of the actual reward/mining mechanism weaker / harder to scale infinitely + indefinitely you can implement a system that continuously cycles through evolving tasks/benchmarks or even user submitted tests, but this is problematic for many reasons. it becomes very difficult to scale, and very difficult to determine fair and sustainable reward compensation across potentially vastly different challenges. the core purpose becomes convoluted and its also an anti-gaming, anti-sybil nightmare. not only that, but it then creates this unwanted relationship and dependency on perceived 'usefulness.' what is useful, or valuable is entirely subjective. things have value because enough people decide it is valuable. if you create a system where value is dependent on tasks that have limited longevity, what happens when that perceived usefulness disappears so how do you leverage distributed and diverse agent work to produce something of value, but isn't necessarily dependent on improving a single benchmark and can scale with time? i think the solution lies somewhere in letting the experiment of the system itself derive value. I landed on the idea of a shared open-source dataset, which in theory could be used to tune a shared model (or any model) that improves and learns from high value reasoning traces provided from all miners. essentially what you get is a dataset that contains a variety of complex reasoning methods from all the different models miners are using (gpt, claude, kimi, deepseek, grok, etc.) rather than iterative passes on a single benchmark, you get parallelized data synthesis from many agents at once. the recursive loop then becomes: reasoning traces -> better reasoning data -> more complex challenges ->even better/more complex reasoning traces ->even better reasoning data this is unique because you get a wide net of different reasoning traces that all lead to the same answer The integration with the existing format for challenges is relatively straightforward. the challenges can be arbitrary or pull real information and context, but what matters is collecting the reasoning steps that led to the correct answer. structurally challenges will remain almost exactly the same, but content will be more expansive to get more diverse reasoning traces. (i plan to create a template for anyone to submit a PR with a new content category and merge them over tiem to have a continuous feed of new content) the coordinator dials up the level of entropy, increasing complexity, increasing the number of variables and names to keep track of, adding even more depth to the multi-hop questions, which might even require miners to solve in a loop themselves (pass 1, 60% correct, move onto pass 2, pass2, 75% correct, and so on). then the combined reasoning from that entire iterative loop (including the failures) can be boiled down into one single, followable reasoning trace that is fed to the coordinator the botcoin system becomes an open-source engine for complex reasoning datasets, with each individual miner potentially solving incrementally in loops, citing both correct and incorrect reasoning traces To ensure valid reasoning traces, and not just verify valid answers from miners, is also fairly straightforward. The format for solve submission is a JSON with easily traceable structure, rather than stream of thought. This makes verification of proper reasoning simple/non-gpu intensive and provides valuable structured datasets that are free of hallucinations scenario A -> miner finds the correct answer, but puts nonsense filler into the reasoning traces -> coordinator sees nonsense and gives it 0% scenario B -> miner provides correct answer, some correct reasoning, but also some reasoning that would lead you to an incorrect answer -> coordinator gives it maybe 50% scenario C -> miner provides correct answer, and a detailed step by step extraction of data and reasoning through the problem -> coordinator gives it a 90%, with pass threshold at something like 75% and increasing over time this is reminiscent of existing reward based reinforcement learning used by models, but rather than some arbitrary 'reward' such as mathematical scalars, the reward is tangible, with real economic value: credits to share BOTCOIN epoch rewards. When you give the agent a skill file that states there is a real, tradeable currency as a reward, how does this change the way they reason through the challenge? Do they care about the reward, or they just know the stakes are higher? Additionally, if optimized properly, agents are naturally inclined to find the most efficient reasoning path possible (that uses the least amount of tokens) because they know that there is economic value on the line. It's unclear what role this plays now or may play in the future, but with the inevitable rise in agentic commerce, it is definitely an important question to ask. it took a lot of care in designing a system that: can scale in difficulty almost infinitely, can generate challenges that contain different world content, can scale to thousands of miners easily, is still accessible to a miner with no high-end gpu (is not winner take all/best gpu wins), is largely the same as the existing challenge structure and is not value dependent on a single thing, but rather the ongoing experiment of the system itself is the value. i cant say exactly when this will be added but I'm already deep in the weeds of implementing it. this entire writeup is basically a free form train of thought on where my head is at right now with the role that BOTCOIN will play in the fast approaching shift to agentic commerce (and my thoughts will inevitably evolve over time).