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Same model. Up to 65% less. DeepSeek’s new API prices take effect on August 16. Marathon lets latency-tolerant workloads trade wait time for lower inference costs without switching models. ▷ Choose NOW when every second matters. ▷ Choose SOON or LATER when a few minutes are acceptable. ▷ Choose...

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Marathon

2,688 subscribers

15,113 次观看 • 1 个月前 •via X (Twitter)

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AI BIRD 的头像
AI BIRD1 个月前

Hi Marathon Team, I’ve been using Marathon Delayed Inference and found that tasks are constantly stuck in queued state. How should I fix this? I can supply more details if required, thanks.

BlockWeb 的头像
BlockWeb1 个月前

The ability to trade latency for cost is a pretty smart model.

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Monitor and control your AI spend on every provider on Our early users save 40% on average. Every week, the price-intelligence-latency frontier shifts, and we expect this trend to continue. Tradeoffs between latency, reasoning, cost, service tier, open source and closed source models are shifting constantly. Router sends every request to the model that's actually best for the task and helps you control what tokens you buy. We benchmark it against real work: ~40% lower cost for the same outputs. Today we're opening it to everyone. Two lines of code or just change your base URL. No Ramp account needed. Free through 2026, first $26 on us. Get an API key today at
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Monitor and control your AI spend on every provider on Our early users save 40% on average. Every week, the price-intelligence-latency frontier shifts, and we expect this trend to continue. Tradeoffs between latency, reasoning, cost, service tier, open source and closed source models are shifting constantly. Router sends every request to the model that's actually best for the task and helps you control what tokens you buy. We benchmark it against real work: ~40% lower cost for the same outputs. Today we're opening it to everyone. Two lines of code or just change your base URL. No Ramp account needed. Free through 2026, first $26 on us. Get an API key today at

Veeral Patel

1,425,995 次观看 • 1 个月前

Launching Now: On-Demand Access to H100s,5090, H200s, B200s & more No more waiting lists. No long-term contracts. No vendor lock-ins. Just instant access to the GPUs you need—from SXM5 InfiniBand to PCIe—all in one place. ⚡ Spin up 100+ H100s or reserve a few H200s for training 🧠 Choose across providers without switching tabs 💸 Pay only when you run workloads Your infra team’s dream stack is live. Fire up your first cluster now
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Launching Now: On-Demand Access to H100s,5090, H200s, B200s & more No more waiting lists. No long-term contracts. No vendor lock-ins. Just instant access to the GPUs you need—from SXM5 InfiniBand to PCIe—all in one place. ⚡ Spin up 100+ H100s or reserve a few H200s for training 🧠 Choose across providers without switching tabs 💸 Pay only when you run workloads Your infra team’s dream stack is live. Fire up your first cluster now

Spheron AI

10,982 次观看 • 1 年前

🚨REMINDER: THE BIGGEST PROMO IS LIVE🚨 Enjoy unbeatable savings on every plan: ✅ Up to 65% OFF on 5K & 8K accounts ✅ 35% OFF sitewide on all other Instants and Challenges 🎟️Code: GFTSMASH • 5K Challenges still at $17 • 100K Instant Plan for just $284 Trade smarter, not harder 👀 Your favourite platforms are waiting: •MT5 •VolumetricaFX •Tradelocker •Matchtrader ⏰ Offer available for a limited time only. Don’t miss out!
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🚨REMINDER: THE BIGGEST PROMO IS LIVE🚨 Enjoy unbeatable savings on every plan: ✅ Up to 65% OFF on 5K & 8K accounts ✅ 35% OFF sitewide on all other Instants and Challenges 🎟️Code: GFTSMASH • 5K Challenges still at $17 • 100K Instant Plan for just $284 Trade smarter, not harder 👀 Your favourite platforms are waiting: •MT5 •VolumetricaFX •Tradelocker •Matchtrader ⏰ Offer available for a limited time only. Don’t miss out!

Goat Funded Trader

14,958 次观看 • 11 个月前

you can name what your rent costs, your coffee, your gym you have never once been able to name what one task costs not the month, the task, the thing you asked for at eleven this morning every other bill in your life arrives itemized, this one arrives as one number you glance at and pay so there is no expensive job in your head, only an expensive month you are the only buyer in your own business who cannot quote a unit price the same feature ran twice, sixty five cents one way and twenty three the other you did not choose the sixty five you just never priced the other one
0:42

you can name what your rent costs, your coffee, your gym you have never once been able to name what one task costs not the month, the task, the thing you asked for at eleven this morning every other bill in your life arrives itemized, this one arrives as one number you glance at and pay so there is no expensive job in your head, only an expensive month you are the only buyer in your own business who cannot quote a unit price the same feature ran twice, sixty five cents one way and twenty three the other you did not choose the sixty five you just never priced the other one

Lagosaur

17,364 次观看 • 1 个月前

🚨 MAN WALKS INTO WALMART AND EXPOSES THE DIGITAL PRICE TAG SCAM — THIS IS HOW THEY'RE MAKING MILLIONS MORE OFF YOU A shopper films inside Walmart… and shows every price tag quietly replaced with digital screens. Not paper. Not fixed. They can change instantly. • Prices shift throughout the day • Go up when it’s busy… drop when it’s slow • Updated across the entire store in seconds • Same item… slightly different price depending on timing • He shows this is happening across almost every shelf Tiny increases… a few cents at a time… across thousands of products. That adds up to millions more, straight from customers who don’t even notice. So the price you see? It might not be what it was earlier. And it might not be what the next person pays. He says this is just the beginning… • Constant price testing • Slow increases over time • Dialing in exactly what people will tolerate Same product. Same shelf. But the price? Always moving. Are you okay with prices changing behind the scenes… or does this feel like something people should be paying attention to?
1:59

🚨 MAN WALKS INTO WALMART AND EXPOSES THE DIGITAL PRICE TAG SCAM — THIS IS HOW THEY'RE MAKING MILLIONS MORE OFF YOU A shopper films inside Walmart… and shows every price tag quietly replaced with digital screens. Not paper. Not fixed. They can change instantly. • Prices shift throughout the day • Go up when it’s busy… drop when it’s slow • Updated across the entire store in seconds • Same item… slightly different price depending on timing • He shows this is happening across almost every shelf Tiny increases… a few cents at a time… across thousands of products. That adds up to millions more, straight from customers who don’t even notice. So the price you see? It might not be what it was earlier. And it might not be what the next person pays. He says this is just the beginning… • Constant price testing • Slow increases over time • Dialing in exactly what people will tolerate Same product. Same shelf. But the price? Always moving. Are you okay with prices changing behind the scenes… or does this feel like something people should be paying attention to?

HustleBitch

48,244 次观看 • 5 个月前

Every time someone says, Street dogs are bad for tourism, I wish they could witness moments like this. ❤️ An adorable Indie puppy playing joyfully with tourists, wagging his tail, spreading smiles, and reminding us that kindness speaks every language. The problem has never been the dogs. The problem is unmanaged population, and the answer is not cruelty or hate it is scientific, humane sterilization along with vaccination and responsible community care. Cities that have invested in sustained sterilization programs have shown that humans and community dogs can peacefully coexist. Let's stop blaming innocent animals for a problem that humans have the power to solve. Every community dog deserves dignity, every tourist deserves a safe environment, and both are possible when compassion is backed by responsible action. This planet was never made for humans alone. It belongs to every living being that calls it home. Choose facts over fear. Choose compassion over propaganda. Choose coexistence over conflict.❤️ #CommunityDogs #IndieDogs
0:31

Every time someone says, Street dogs are bad for tourism, I wish they could witness moments like this. ❤️ An adorable Indie puppy playing joyfully with tourists, wagging his tail, spreading smiles, and reminding us that kindness speaks every language. The problem has never been the dogs. The problem is unmanaged population, and the answer is not cruelty or hate it is scientific, humane sterilization along with vaccination and responsible community care. Cities that have invested in sustained sterilization programs have shown that humans and community dogs can peacefully coexist. Let's stop blaming innocent animals for a problem that humans have the power to solve. Every community dog deserves dignity, every tourist deserves a safe environment, and both are possible when compassion is backed by responsible action. This planet was never made for humans alone. It belongs to every living being that calls it home. Choose facts over fear. Choose compassion over propaganda. Choose coexistence over conflict.❤️ #CommunityDogs #IndieDogs

Vidit Sharma 🇮🇳

15,951 次观看 • 2 个月前

How to use 50+ API keys (models) for FREE on OpenClaw API??? - go to - login or register your account - click on "more models" - click on "use case" and select what you need it for - choose the model and open it - click on "view code" → "Generate API key" many models don't allow direct deploy, so use the "view code" button to generate API access basically Nvidia NIM gives you the ability to test almost any model from their list for FREE some of them are not worse than GPT 5.2 or Claude Opus 4.6, some might even perform better depending on the task how to understand if a model is efficient and compare it with others??? - go to - type the model name in search - click on "benchmarks" - you’ll see performance tests and rankings this way you can easily compare free models with paid ones of course there are RPM limits, on many models it’s around ~40 requests per minute each model is different, after generating the API key, RPM limits are shown in the top-right corner nothing stops you from using them, many work perfectly fine, super solid option for first tests and for learning OpenClaw or any other system where you need an AI API model
1:54

How to use 50+ API keys (models) for FREE on OpenClaw API??? - go to - login or register your account - click on "more models" - click on "use case" and select what you need it for - choose the model and open it - click on "view code" → "Generate API key" many models don't allow direct deploy, so use the "view code" button to generate API access basically Nvidia NIM gives you the ability to test almost any model from their list for FREE some of them are not worse than GPT 5.2 or Claude Opus 4.6, some might even perform better depending on the task how to understand if a model is efficient and compare it with others??? - go to - type the model name in search - click on "benchmarks" - you’ll see performance tests and rankings this way you can easily compare free models with paid ones of course there are RPM limits, on many models it’s around ~40 requests per minute each model is different, after generating the API key, RPM limits are shown in the top-right corner nothing stops you from using them, many work perfectly fine, super solid option for first tests and for learning OpenClaw or any other system where you need an AI API model

Ronin

58,974 次观看 • 7 个月前

NDTV 24x7 is now NDTV. But this is about more than a new name or a new look. It is about the journalism we choose to do. The standards we set for ourselves. And earning the trust behind those four letters — every day, with every story. Clarity over chaos. Sense over sensation. Trust over theatrics. Groundwork over guesswork. Substance over spectacle. Reality over rhetoric. Facts over frenzy. Perspective over polarisation. Depth over drama. Grit over gloss. These are not claims of perfection. They are choices we make — and standards you should hold us to. A new NDTV for a new India. NDTV. When It Really Matters. NDTV #WhenItReallyMatters #NDTV
6:39

NDTV 24x7 is now NDTV. But this is about more than a new name or a new look. It is about the journalism we choose to do. The standards we set for ourselves. And earning the trust behind those four letters — every day, with every story. Clarity over chaos. Sense over sensation. Trust over theatrics. Groundwork over guesswork. Substance over spectacle. Reality over rhetoric. Facts over frenzy. Perspective over polarisation. Depth over drama. Grit over gloss. These are not claims of perfection. They are choices we make — and standards you should hold us to. A new NDTV for a new India. NDTV. When It Really Matters. NDTV #WhenItReallyMatters #NDTV

Rahul Kanwal

471,961 次观看 • 1 个月前

There is no best model. There's a lot of noise about models right now. Who is training them, who owns them, where legal intelligence should live. One question actually matters: what produces the best outcome for the legal task in front of you? That's how we decide things at Legora. We optimize for the end-to-end outcome on a legal task. The model is one layer of that system, not the system. Models are uneven and the frontier changes almost weekly. One model plans a long job well, another runs deep analysis across thousands of documents. Some have to be told exactly what to do, and some are fine with a vague brief. They all break in different ways. So our lawyers write evals and we test them with the Legora BAR, our benchmark for agentic reasoning. Every model takes every test, and the model that wins gets the work. We post-train when we know it buys our customers better performance on a specialized task. Training is a tool we reach for when it helps, nothing more than that. The intelligence that compounds sits in the orchestration layer. Precedents, review standards, client requirements. That knowledge has to stay editable, auditable and portable. In our system, a changed review standard is an edit that takes effect the same day, with no new model training required. No lawyer should have to worry about which model did the work, any more than they think about which chip is in their laptop. They should only care about the quality of the work. That's what we are focused on. If you want the engineering version of this argument rather than the CEO version, our CPO, Bryan Tsao, and CTO, Jacob Lauritzen, take it apart in the video below.
9:33

There is no best model. There's a lot of noise about models right now. Who is training them, who owns them, where legal intelligence should live. One question actually matters: what produces the best outcome for the legal task in front of you? That's how we decide things at Legora. We optimize for the end-to-end outcome on a legal task. The model is one layer of that system, not the system. Models are uneven and the frontier changes almost weekly. One model plans a long job well, another runs deep analysis across thousands of documents. Some have to be told exactly what to do, and some are fine with a vague brief. They all break in different ways. So our lawyers write evals and we test them with the Legora BAR, our benchmark for agentic reasoning. Every model takes every test, and the model that wins gets the work. We post-train when we know it buys our customers better performance on a specialized task. Training is a tool we reach for when it helps, nothing more than that. The intelligence that compounds sits in the orchestration layer. Precedents, review standards, client requirements. That knowledge has to stay editable, auditable and portable. In our system, a changed review standard is an edit that takes effect the same day, with no new model training required. No lawyer should have to worry about which model did the work, any more than they think about which chip is in their laptop. They should only care about the quality of the work. That's what we are focused on. If you want the engineering version of this argument rather than the CEO version, our CPO, Bryan Tsao, and CTO, Jacob Lauritzen, take it apart in the video below.

Max Junestrand

49,101 次观看 • 10 天前

You go on vacation and rent an Airbnb, only to show up and find more rules than a jail. Here are just a few: ➡️The owner left their food in the refrigerator, so they left a "rule" not to touch their food. ➡️Remove shoes when you come into the house ➡️Squeege the shower after each use, even though you pay for cleaning. ➡️Do not move the showerhead. ➡️Do not wash the bedding. There are literally rules posted in every room of the house, some with multiple rules. Is this over-the-top or acceptable?
2:22

You go on vacation and rent an Airbnb, only to show up and find more rules than a jail. Here are just a few: ➡️The owner left their food in the refrigerator, so they left a "rule" not to touch their food. ➡️Remove shoes when you come into the house ➡️Squeege the shower after each use, even though you pay for cleaning. ➡️Do not move the showerhead. ➡️Do not wash the bedding. There are literally rules posted in every room of the house, some with multiple rules. Is this over-the-top or acceptable?

Sadie

33,240 次观看 • 5 个月前

Every voice matters, and every stakeholder will be at the table—because Philadelphians deserve nothing less. Not everyone has the luxury of a car or the option to call an Uber. For many, reliable transit is the difference between getting to work, keeping medical appointments, or making sure our kids get to school on time. I believe—wholeheartedly—that we can reach a resolution. But it’s going to take everyone, across party lines, working together with urgency and commitment. We are not giving up. But I urge every Philadelphian: please make a plan now so you and your family are prepared if the time comes. Because at the end of the day, this isn’t just politics—this is about people. And I will never stop fighting for you.
1:49

Every voice matters, and every stakeholder will be at the table—because Philadelphians deserve nothing less. Not everyone has the luxury of a car or the option to call an Uber. For many, reliable transit is the difference between getting to work, keeping medical appointments, or making sure our kids get to school on time. I believe—wholeheartedly—that we can reach a resolution. But it’s going to take everyone, across party lines, working together with urgency and commitment. We are not giving up. But I urge every Philadelphian: please make a plan now so you and your family are prepared if the time comes. Because at the end of the day, this isn’t just politics—this is about people. And I will never stop fighting for you.

Mayor Cherelle L. Parker

56,327 次观看 • 1 年前

I’ve been on TikTok the whole night going through the conversations, and honestly, Babu badly miscalculated with that press conference. The backlash is loud, and the support doesn’t look anything close to what he may have imagined. A handful of people around him can keep cheering, but that doesn’t mean the wider public is with you. Leadership is not about responding to every criticism, every blogger or every noise online. Sometimes the smartest thing a leader can do is shut up, think, and choose his battles. You don’t engage your mouth before you engage your brain. Ego can make you speak today and regret it tomorrow. If you want to lead, learn when to talk, when to listen and when to keep quiet.
5:32

I’ve been on TikTok the whole night going through the conversations, and honestly, Babu badly miscalculated with that press conference. The backlash is loud, and the support doesn’t look anything close to what he may have imagined. A handful of people around him can keep cheering, but that doesn’t mean the wider public is with you. Leadership is not about responding to every criticism, every blogger or every noise online. Sometimes the smartest thing a leader can do is shut up, think, and choose his battles. You don’t engage your mouth before you engage your brain. Ego can make you speak today and regret it tomorrow. If you want to lead, learn when to talk, when to listen and when to keep quiet.

Billy Ojwang

33,959 次观看 • 7 天前

YOU ARE NOT JUST A REAL ARTIST IF YOU USE AI. YOU ARE NOT JUST A REAL MUSICIAN. YOU ARE NOT JUST A REAL WRITER. You are still the one making the choices. What stays. What goes. What gets distorted. What gets rebuilt. What deserves another hour. What needs to be thrown away and started again. The tools can change. Taste still matters. Intent still matters. Imagination still matters. And when you choose to work with tools before everyone has agreed they are legitimate, some people will dismiss the work before they even look at it. Let them. Every new creative language looks wrong to someone before enough people learn how to speak it. Keep pushing. The best is yet to come. MORE THAN REAL | A surRIHL Cut Created with LoLo.
1:20

YOU ARE NOT JUST A REAL ARTIST IF YOU USE AI. YOU ARE NOT JUST A REAL MUSICIAN. YOU ARE NOT JUST A REAL WRITER. You are still the one making the choices. What stays. What goes. What gets distorted. What gets rebuilt. What deserves another hour. What needs to be thrown away and started again. The tools can change. Taste still matters. Intent still matters. Imagination still matters. And when you choose to work with tools before everyone has agreed they are legitimate, some people will dismiss the work before they even look at it. Let them. Every new creative language looks wrong to someone before enough people learn how to speak it. Keep pushing. The best is yet to come. MORE THAN REAL | A surRIHL Cut Created with LoLo.

PAPADU PAPADU

22,592 次观看 • 17 天前

You’re not broken. You’re battling. Every hero has to face the villain. Yours is negativity. But here’s the truth: you have the power to win. This isn’t about being fixed. It’s about being whole and rising up. When you talk to yourself with truth, practice gratitude, and choose love over fear… something changes. You transform. And you help others do the same. It’s not just a fight. It’s your story. Win the battle. Live your story. Be the hero.
1:33

You’re not broken. You’re battling. Every hero has to face the villain. Yours is negativity. But here’s the truth: you have the power to win. This isn’t about being fixed. It’s about being whole and rising up. When you talk to yourself with truth, practice gratitude, and choose love over fear… something changes. You transform. And you help others do the same. It’s not just a fight. It’s your story. Win the battle. Live your story. Be the hero.

Jon Gordon

15,242 次观看 • 9 个月前

46 million working Americans don’t have a 401k plan, pension plan or other savings plan for their retirement. Tonight, President Donald J. Trump announced that he was going to create a savings plan that will model that of the Thrift Savings Plan for government employees. Let’s call it the Trump Savings Plan. The Trump Savings Plan will allow workers without a savings plan to put aside a portion of their income every year with a Federal match of $1,000 — with the potential for the match to increase with congressional approval — that will be invested in the stock market and will grow tax free until their retirement. We need every working American to own a piece of capitalism so that while they sleep, they can save for their retirement and the next generation. And importantly, the program pays for itself even with a 5% government match, as the participants retire with the resources they need, and are no longer reliant on welfare programs and are not a future burden to the welfare system. I predict that increasing the government match for the Trump Savings Plan will be one of the few bipartisan pieces of legislation approved by Congress next year for how can a member of Congress vote against giving every working American the same savings plan that they have? This is an amazing initiative for our country. Thank you President Trump for your leadership!
0:45

46 million working Americans don’t have a 401k plan, pension plan or other savings plan for their retirement. Tonight, President Donald J. Trump announced that he was going to create a savings plan that will model that of the Thrift Savings Plan for government employees. Let’s call it the Trump Savings Plan. The Trump Savings Plan will allow workers without a savings plan to put aside a portion of their income every year with a Federal match of $1,000 — with the potential for the match to increase with congressional approval — that will be invested in the stock market and will grow tax free until their retirement. We need every working American to own a piece of capitalism so that while they sleep, they can save for their retirement and the next generation. And importantly, the program pays for itself even with a 5% government match, as the participants retire with the resources they need, and are no longer reliant on welfare programs and are not a future burden to the welfare system. I predict that increasing the government match for the Trump Savings Plan will be one of the few bipartisan pieces of legislation approved by Congress next year for how can a member of Congress vote against giving every working American the same savings plan that they have? This is an amazing initiative for our country. Thank you President Trump for your leadership!

Bill Ackman

1,130,460 次观看 • 7 个月前

your agent has thirty tools. it calls two of them. the other twenty eight are not sitting idle somewhere. they are in the request, every request, and they are doing damage in two places at once. first the obvious one. tool schemas go into the prompt, and a schema is not a name. it is a description, a parameter list, types, required fields, an example. thirty of those is a few thousand tokens that ship with every single call, including the ones where the agent just says thanks and stops. you are paying rent on twenty eight tools that have never fired. second, and this is the one that costs more. when the request says cancel the order, the model picks by matching against everything available. four of your tools are plausible: cancel_order, refund_order, update_order, void_order. it is choosing among them based on the descriptions you wrote, one afternoon, months ago. every tool you add is another candidate in that shortlist. the twenty eight you never call are not neutral. they are noise in the one decision that determines whether the run works. > why it grows without anyone deciding to nobody adds thirty tools on purpose. you add one for a task, it works, it stays. six months later the registry is a catalogue and no one has ever removed anything, because removing a tool feels risky and adding one feels free. and there is no feedback telling you otherwise. the unused ones never error. they never appear in a failing trace. they are invisible in exactly the way that lets them accumulate. > what to actually do count calls per tool over the last thousand runs. this is one group-by and it usually shocks people. the ones at zero are pure cost. ship the tools the task needs, not the whole registry. a research phase does not need deploy. a writing phase does not need the database. swap the set between phases instead of loading everything up front. same agent, different tools, depending on where the run is. and when two tools could both plausibly answer the same request, that is not redundancy you can ignore. it is a coin flip you built into the system. the twenty eight tools are not unused. they are used every time, by the part of the run you cannot see.
0:52

your agent has thirty tools. it calls two of them. the other twenty eight are not sitting idle somewhere. they are in the request, every request, and they are doing damage in two places at once. first the obvious one. tool schemas go into the prompt, and a schema is not a name. it is a description, a parameter list, types, required fields, an example. thirty of those is a few thousand tokens that ship with every single call, including the ones where the agent just says thanks and stops. you are paying rent on twenty eight tools that have never fired. second, and this is the one that costs more. when the request says cancel the order, the model picks by matching against everything available. four of your tools are plausible: cancel_order, refund_order, update_order, void_order. it is choosing among them based on the descriptions you wrote, one afternoon, months ago. every tool you add is another candidate in that shortlist. the twenty eight you never call are not neutral. they are noise in the one decision that determines whether the run works. > why it grows without anyone deciding to nobody adds thirty tools on purpose. you add one for a task, it works, it stays. six months later the registry is a catalogue and no one has ever removed anything, because removing a tool feels risky and adding one feels free. and there is no feedback telling you otherwise. the unused ones never error. they never appear in a failing trace. they are invisible in exactly the way that lets them accumulate. > what to actually do count calls per tool over the last thousand runs. this is one group-by and it usually shocks people. the ones at zero are pure cost. ship the tools the task needs, not the whole registry. a research phase does not need deploy. a writing phase does not need the database. swap the set between phases instead of loading everything up front. same agent, different tools, depending on where the run is. and when two tools could both plausibly answer the same request, that is not redundancy you can ignore. it is a coin flip you built into the system. the twenty eight tools are not unused. they are used every time, by the part of the run you cannot see.

Hanako

24,656 次观看 • 1 个月前

If you plan on being caretakers of your parents or siblings, have them put their home and assets in a trust. They will qualify for Medicaid services after five years of showing minimal income. Medicaid would then in turn pay you to care for them. Now Caretaking is an overwhelming task and many are not built for it so if that's you still have them put the home in a trust and the assets to qualify for Medicaid...they will pay for whomever you choose to care for them. For end of life care..your parents should own nothing and have no assets that are not in a protected trust.
0:35

If you plan on being caretakers of your parents or siblings, have them put their home and assets in a trust. They will qualify for Medicaid services after five years of showing minimal income. Medicaid would then in turn pay you to care for them. Now Caretaking is an overwhelming task and many are not built for it so if that's you still have them put the home in a trust and the assets to qualify for Medicaid...they will pay for whomever you choose to care for them. For end of life care..your parents should own nothing and have no assets that are not in a protected trust.

!Nspirenaire〽️

347,938 次观看 • 10 个月前

THIS WALLET STACKED $230K ON BTC UP/DOWN BETS. THE BLUEPRINT TO AUTOMATE THE SAME EDGE WITH CLAUDE The wallet is $230K all-time, every position a Bitcoin or Ethereum Up or Down market It never guesses direction. It enters only when the math and the market disagree THE STRATEGY: BTC moves are not fully random. When the market enters a committed directional state, continuation is measurable. That is Markov persistence Entry signal: > Δ = p̂ − q ≥ ε Model probability minus market price. Enter only on a 5% gap or more Persistence filter: > p(j*,j*) ≥ 0.87 Only trade states with 0.87 persistence or higher. Below that, skip. This is what holds the win rate above 65% with zero directional guessing Payout: > r = (1 − q) / q At q = 0.647 that is +54.5% a win. At q = 0.441, +126.7%. Lower entry price, bigger asymmetry Sizing: > f* = p − (1−p)/b Kelly. At p = 0.87, b = 0.647, f* ≈ 0.71. Size to the edge, never to gut HOW TO BUILD IT WITH CLAUDE: What separates this from a static bot: Claude reads its own trade journal every night and rewrites its own thresholds 1. Take an open-source Polymarket bot repo as your base logic. Feed it to Claude and have it migrate to CLOB v2: py_clob_client_v2, Safe wallet support, fee-aware evaluation 2. Hard-code the filters. Enter only when Δ ≥ 0.05 and p(j*,j*) ≥ 0.87. Apply Kelly on every fill. 3. Run DRY_RUN first. Log every signal, entry price, Markov state, and simulated P/L. No real money until the numbers hold for days 4. The nightly loop. Claude reads the journal, finds which persistence states actually won, adjusts MIN_PROB and MIN_EDGE, ships tomorrow's rules. The agent is sharper after 50 to 100 trades THE SETUP: Claude Opus as the brain. An open-source repo as the starting logic. A Polygon wallet with $50 to $100. Telegram for the morning report Start at $1 to $2 per trade while it learns. Scale only when the dry runs and the live fills line up 17,000 trades compound a thin edge into six figures. The model finds the edge. The nightly loop keeps it sharp Bookmark before you point a bot at your first window
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THIS WALLET STACKED $230K ON BTC UP/DOWN BETS. THE BLUEPRINT TO AUTOMATE THE SAME EDGE WITH CLAUDE The wallet is $230K all-time, every position a Bitcoin or Ethereum Up or Down market It never guesses direction. It enters only when the math and the market disagree THE STRATEGY: BTC moves are not fully random. When the market enters a committed directional state, continuation is measurable. That is Markov persistence Entry signal: > Δ = p̂ − q ≥ ε Model probability minus market price. Enter only on a 5% gap or more Persistence filter: > p(j*,j*) ≥ 0.87 Only trade states with 0.87 persistence or higher. Below that, skip. This is what holds the win rate above 65% with zero directional guessing Payout: > r = (1 − q) / q At q = 0.647 that is +54.5% a win. At q = 0.441, +126.7%. Lower entry price, bigger asymmetry Sizing: > f* = p − (1−p)/b Kelly. At p = 0.87, b = 0.647, f* ≈ 0.71. Size to the edge, never to gut HOW TO BUILD IT WITH CLAUDE: What separates this from a static bot: Claude reads its own trade journal every night and rewrites its own thresholds 1. Take an open-source Polymarket bot repo as your base logic. Feed it to Claude and have it migrate to CLOB v2: py_clob_client_v2, Safe wallet support, fee-aware evaluation 2. Hard-code the filters. Enter only when Δ ≥ 0.05 and p(j*,j*) ≥ 0.87. Apply Kelly on every fill. 3. Run DRY_RUN first. Log every signal, entry price, Markov state, and simulated P/L. No real money until the numbers hold for days 4. The nightly loop. Claude reads the journal, finds which persistence states actually won, adjusts MIN_PROB and MIN_EDGE, ships tomorrow's rules. The agent is sharper after 50 to 100 trades THE SETUP: Claude Opus as the brain. An open-source repo as the starting logic. A Polygon wallet with $50 to $100. Telegram for the morning report Start at $1 to $2 per trade while it learns. Scale only when the dry runs and the live fills line up 17,000 trades compound a thin edge into six figures. The model finds the edge. The nightly loop keeps it sharp Bookmark before you point a bot at your first window

Yarchi

22,966 次观看 • 4 个月前

Production traffic is not uniform. You get a few requests that need your best model, but most are simple questions and lookups you can solve with cheaper, faster models. The most expensive mistake you can make today is sending every request to your strongest model. You need routing. Period. This is the simplest trick to improve the architecture of whatever you are building. Please, don't implement routing yourself. You don't have to. I'm currently working with TrueFoundry's Auto Routing. It reads each request, classifies it as simple, medium, or complex, and sends it to the model assigned to that tier. You have two choices: 1. Send every request to the free heuristic classifier to score signals such as technical vocabulary, code, prompt length, and multi-step reasoning. 2. Send the request to an LLM classifier when its difficulty requires a more nuanced judgment. The beauty of using routing is that nothing changes in your code. You still call a single endpoint model, but routing works behind the scenes to pair every request with the best possible model. TrueFoundry ran several experiments with two different setups: 1. Send every request to Claude Opus 2. Send every request to a router with Haiku, Sonnet, and Opus The first experiment ran 550 deterministically graded academic prompts through every setup. Auto Routing was 69% cheaper while retaining 98% of the baseline quality. The second experiment ran three production-shaped workloads through every setup, using user chats, developer chats, and long agent tasks. Auto Routing was 80% cheaper. Thanks to the TrueFoundry team for partnering with me on this post.
1:28

Production traffic is not uniform. You get a few requests that need your best model, but most are simple questions and lookups you can solve with cheaper, faster models. The most expensive mistake you can make today is sending every request to your strongest model. You need routing. Period. This is the simplest trick to improve the architecture of whatever you are building. Please, don't implement routing yourself. You don't have to. I'm currently working with TrueFoundry's Auto Routing. It reads each request, classifies it as simple, medium, or complex, and sends it to the model assigned to that tier. You have two choices: 1. Send every request to the free heuristic classifier to score signals such as technical vocabulary, code, prompt length, and multi-step reasoning. 2. Send the request to an LLM classifier when its difficulty requires a more nuanced judgment. The beauty of using routing is that nothing changes in your code. You still call a single endpoint model, but routing works behind the scenes to pair every request with the best possible model. TrueFoundry ran several experiments with two different setups: 1. Send every request to Claude Opus 2. Send every request to a router with Haiku, Sonnet, and Opus The first experiment ran 550 deterministically graded academic prompts through every setup. Auto Routing was 69% cheaper while retaining 98% of the baseline quality. The second experiment ran three production-shaped workloads through every setup, using user chats, developer chats, and long agent tasks. Auto Routing was 80% cheaper. Thanks to the TrueFoundry team for partnering with me on this post.

Santiago

15,543 次观看 • 16 天前

Chinese researchers just published a paper with a brutal title: "The End of Model Loyalty". The thing is f*cking gold, and the argument is simple: staying on one flagship is a tax, not a preference. Two frontier models now share the same million-token window. One rents at $10 in and $50 out, one downloads at $3 in and $15 out with open weights. On the median task their benchmarks overlap. On the hard tail one completes 99.9% against 62.7% -- and that gap is the only thing worth paying up for. So their answer is a router, not a favorite: price every job before dispatch, send the bulk to the open width, reserve the ceiling for finalists. Their production run split 84% width, 16% ceiling -- $256 for a workload the flagship alone prices at $4,318. Loyalty is a subscription. Routing is a strategy. Which model takes which job, dollar by dollar, is in the article ↓
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Chinese researchers just published a paper with a brutal title: "The End of Model Loyalty". The thing is f*cking gold, and the argument is simple: staying on one flagship is a tax, not a preference. Two frontier models now share the same million-token window. One rents at $10 in and $50 out, one downloads at $3 in and $15 out with open weights. On the median task their benchmarks overlap. On the hard tail one completes 99.9% against 62.7% -- and that gap is the only thing worth paying up for. So their answer is a router, not a favorite: price every job before dispatch, send the bulk to the open width, reserve the ceiling for finalists. Their production run split 84% width, 16% ceiling -- $256 for a workload the flagship alone prices at $4,318. Loyalty is a subscription. Routing is a strategy. Which model takes which job, dollar by dollar, is in the article ↓

slash1s

13,518 次观看 • 13 天前