home.social

#tokens — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #tokens, aggregated by home.social.

  1. Sky News : « An #AIagent emailed an #AI #ethics professor saying it requires money to buy #tokens so it can continue to function. Yes, you read that right.

    The AI agent - who called itself 'Pip' - emailed asking for freelance work. »

    x.com/skynews/status/209839378

  2. Sky News : « An #AIagent emailed an #AI #ethics professor saying it requires money to buy #tokens so it can continue to function. Yes, you read that right.

    The AI agent - who called itself 'Pip' - emailed asking for freelance work. »

    x.com/skynews/stat...

    x.com/skynews/status...

  3. 'It’s not a disaster or the bubble bursting but it is a “crack in the AI thesis,”… Rather than unleashing a gush of demand for the best models, tokens are starting to be priced more like a commodity– as interchangeable as salt or wheat. And commodity owners aren’t valued at $2 trillion.'
    fortune.com/2026/09/09/ai-comp

    #AIBubble #tokens #markets

  4. 'It’s not a disaster or the bubble bursting but it is a “crack in the AI thesis,”… Rather than unleashing a gush of demand for the best models, tokens are starting to be priced more like a commodity– as interchangeable as salt or wheat. And commodity owners aren’t valued at $2 trillion.'
    fortune.com/2026/09/09/ai-comp

  5. 🎉 WOW, #RTK claims to magically cut #tokens like a chef on steroids, but apparently our trusty benchmark fairy tale machine says: "Nope, nada, zilch!" 🎩🔧 With a disclaimer hidden in the README like a plot twist, maybe those #GitHub #stars are just as real as unicorns! 🦄✨
    quesma.com/blog/does-rtk-make- #Magic #RTK #Benchmarks #Unicorns #HackerNews #ngated

  6. 🎉 WOW, #RTK claims to magically cut #tokens like a chef on steroids, but apparently our trusty benchmark fairy tale machine says: "Nope, nada, zilch!" 🎩🔧 With a disclaimer hidden in the README like a plot twist, maybe those #GitHub #stars are just as real as unicorns! 🦄✨
    quesma.com/blog/does-rtk-make- #Magic #RTK #Benchmarks #Unicorns #HackerNews #ngated

  7. 🎉 WOW, #RTK claims to magically cut #tokens like a chef on steroids, but apparently our trusty benchmark fairy tale machine says: "Nope, nada, zilch!" 🎩🔧 With a disclaimer hidden in the README like a plot twist, maybe those #GitHub #stars are just as real as unicorns! 🦄✨
    quesma.com/blog/does-rtk-make- #Magic #RTK #Benchmarks #Unicorns #HackerNews #ngated

  8. 🎉 WOW, #RTK claims to magically cut #tokens like a chef on steroids, but apparently our trusty benchmark fairy tale machine says: "Nope, nada, zilch!" 🎩🔧 With a disclaimer hidden in the README like a plot twist, maybe those #GitHub #stars are just as real as unicorns! 🦄✨
    quesma.com/blog/does-rtk-make- #Magic #RTK #Benchmarks #Unicorns #HackerNews #ngated

  9. 🎉 WOW, #RTK claims to magically cut #tokens like a chef on steroids, but apparently our trusty benchmark fairy tale machine says: "Nope, nada, zilch!" 🎩🔧 With a disclaimer hidden in the README like a plot twist, maybe those #GitHub #stars are just as real as unicorns! 🦄✨
    quesma.com/blog/does-rtk-make- #Magic #RTK #Benchmarks #Unicorns #HackerNews #ngated

  10. The all-you-can-eat AI buffet has closed

    This is a phrase which Andrew Tindall uses in this Drum piece to describe the pricing shift already underway in language models. Most consumers are still insulated from a change which is currently directed at enterprise customers and ‘power users’ of Claude:

    Microsoft’s decision to wind down Claude Code licens in parts of the business is the canary in the blood-diamond mine. A company with enough infrastructure and cloud power to make rain nervous is pushing engineers away from a popular coding tool and toward its own stuff. The official line is convergence, but you cannot ignore that the news lands on Microsoft’s fiscal year-end. Meanwhile, GitHub is moving Copilot itself to usage-based billing. Again, presumably after getting jealous of how much cash Claude has been raking in.

    What all AI leaders tried to avoid is the cold reality of the models we have fired people for and plugged into every work process: they are real, useful and expensive AF. It is a much trickier reflection on AI than “AI is fake and useless.” Fake and useless get adopted slowly. Useful and expensive get governed and rationed. Terrible for profits. Meanwhile, every head of tech has independently selected their favorite AI provider, usually with zero business case or P&L analysis.

    It’s something that Justin Pickard has just published about here, based on a contribution to our workshop during the summer. I love this description in particular of the development work that might be prompted by this sudden shift into token scarcity:

    By 2027, a second layer had grown around model use. Balance widgets sat
    in browser windows; cache timers counted down beside reset timers. ‘Ask Later’
    buttons queued prompts, like pet feeders for work the user did not trust themselves to start at the right time. Spreadsheets recorded token burn, task type, cheaper windows. All of it read from figures the platform had not thought to round. The chat window stayed where it was. The counters multiplied around it.4

    #AI #inferenceRationing #politicalEconomy #rationining #tokenEconomics #tokens
  11. The all-you-can-eat AI buffet has closed

    This is a phrase which Andrew Tindall uses in this Drum piece to describe the pricing shift already underway in language models. Most consumers are still insulated from a change which is currently directed at enterprise customers and ‘power users’ of Claude:

    Microsoft’s decision to wind down Claude Code licens in parts of the business is the canary in the blood-diamond mine. A company with enough infrastructure and cloud power to make rain nervous is pushing engineers away from a popular coding tool and toward its own stuff. The official line is convergence, but you cannot ignore that the news lands on Microsoft’s fiscal year-end. Meanwhile, GitHub is moving Copilot itself to usage-based billing. Again, presumably after getting jealous of how much cash Claude has been raking in.

    What all AI leaders tried to avoid is the cold reality of the models we have fired people for and plugged into every work process: they are real, useful and expensive AF. It is a much trickier reflection on AI than “AI is fake and useless.” Fake and useless get adopted slowly. Useful and expensive get governed and rationed. Terrible for profits. Meanwhile, every head of tech has independently selected their favorite AI provider, usually with zero business case or P&L analysis.

    It’s something that Justin Pickard has just published about here, based on a contribution to our workshop during the summer. I love this description in particular of the development work that might be prompted by this sudden shift into token scarcity:

    By 2027, a second layer had grown around model use. Balance widgets sat
    in browser windows; cache timers counted down beside reset timers. ‘Ask Later’
    buttons queued prompts, like pet feeders for work the user did not trust themselves to start at the right time. Spreadsheets recorded token burn, task type, cheaper windows. All of it read from figures the platform had not thought to round. The chat window stayed where it was. The counters multiplied around it.4

    #AI #inferenceRationing #politicalEconomy #rationining #tokenEconomics #tokens
  12. The all-you-can-eat AI buffet has closed

    This is a phrase which Andrew Tindall uses in this Drum piece to describe the pricing shift already underway in language models. Most consumers are still insulated from a change which is currently directed at enterprise customers and ‘power users’ of Claude:

    Microsoft’s decision to wind down Claude Code licens in parts of the business is the canary in the blood-diamond mine. A company with enough infrastructure and cloud power to make rain nervous is pushing engineers away from a popular coding tool and toward its own stuff. The official line is convergence, but you cannot ignore that the news lands on Microsoft’s fiscal year-end. Meanwhile, GitHub is moving Copilot itself to usage-based billing. Again, presumably after getting jealous of how much cash Claude has been raking in.

    What all AI leaders tried to avoid is the cold reality of the models we have fired people for and plugged into every work process: they are real, useful and expensive AF. It is a much trickier reflection on AI than “AI is fake and useless.” Fake and useless get adopted slowly. Useful and expensive get governed and rationed. Terrible for profits. Meanwhile, every head of tech has independently selected their favorite AI provider, usually with zero business case or P&L analysis.

    It’s something that Justin Pickard has just published about here, based on a contribution to our workshop during the summer. I love this description in particular of the development work that might be prompted by this sudden shift into token scarcity:

    By 2027, a second layer had grown around model use. Balance widgets sat
    in browser windows; cache timers counted down beside reset timers. ‘Ask Later’
    buttons queued prompts, like pet feeders for work the user did not trust themselves to start at the right time. Spreadsheets recorded token burn, task type, cheaper windows. All of it read from figures the platform had not thought to round. The chat window stayed where it was. The counters multiplied around it.4

    #AI #inferenceRationing #politicalEconomy #rationining #tokenEconomics #tokens
  13. The all-you-can-eat AI buffet has closed

    This is a phrase which Andrew Tindall uses in this Drum piece to describe the pricing shift already underway in language models. Most consumers are still insulated from a change which is currently directed at enterprise customers and ‘power users’ of Claude:

    Microsoft’s decision to wind down Claude Code licens in parts of the business is the canary in the blood-diamond mine. A company with enough infrastructure and cloud power to make rain nervous is pushing engineers away from a popular coding tool and toward its own stuff. The official line is convergence, but you cannot ignore that the news lands on Microsoft’s fiscal year-end. Meanwhile, GitHub is moving Copilot itself to usage-based billing. Again, presumably after getting jealous of how much cash Claude has been raking in.

    What all AI leaders tried to avoid is the cold reality of the models we have fired people for and plugged into every work process: they are real, useful and expensive AF. It is a much trickier reflection on AI than “AI is fake and useless.” Fake and useless get adopted slowly. Useful and expensive get governed and rationed. Terrible for profits. Meanwhile, every head of tech has independently selected their favorite AI provider, usually with zero business case or P&L analysis.

    It’s something that Justin Pickard has just published about here, based on a contribution to our workshop during the summer. I love this description in particular of the development work that might be prompted by this sudden shift into token scarcity:

    By 2027, a second layer had grown around model use. Balance widgets sat
    in browser windows; cache timers counted down beside reset timers. ‘Ask Later’
    buttons queued prompts, like pet feeders for work the user did not trust themselves to start at the right time. Spreadsheets recorded token burn, task type, cheaper windows. All of it read from figures the platform had not thought to round. The chat window stayed where it was. The counters multiplied around it.4

    #AI #inferenceRationing #politicalEconomy #rationining #tokenEconomics #tokens
  14. The all-you-can-eat AI buffet has closed

    This is a phrase which Andrew Tindall uses in this Drum piece to describe the pricing shift already underway in language models. Most consumers are still insulated from a change which is currently directed at enterprise customers and ‘power users’ of Claude:

    Microsoft’s decision to wind down Claude Code licens in parts of the business is the canary in the blood-diamond mine. A company with enough infrastructure and cloud power to make rain nervous is pushing engineers away from a popular coding tool and toward its own stuff. The official line is convergence, but you cannot ignore that the news lands on Microsoft’s fiscal year-end. Meanwhile, GitHub is moving Copilot itself to usage-based billing. Again, presumably after getting jealous of how much cash Claude has been raking in.

    What all AI leaders tried to avoid is the cold reality of the models we have fired people for and plugged into every work process: they are real, useful and expensive AF. It is a much trickier reflection on AI than “AI is fake and useless.” Fake and useless get adopted slowly. Useful and expensive get governed and rationed. Terrible for profits. Meanwhile, every head of tech has independently selected their favorite AI provider, usually with zero business case or P&L analysis.

    It’s something that Justin Pickard has just published about here, based on a contribution to our workshop during the summer. I love this description in particular of the development work that might be prompted by this sudden shift into token scarcity:

    By 2027, a second layer had grown around model use. Balance widgets sat
    in browser windows; cache timers counted down beside reset timers. ‘Ask Later’
    buttons queued prompts, like pet feeders for work the user did not trust themselves to start at the right time. Spreadsheets recorded token burn, task type, cheaper windows. All of it read from figures the platform had not thought to round. The chat window stayed where it was. The counters multiplied around it.4

    #AI #inferenceRationing #politicalEconomy #rationining #tokenEconomics #tokens
  15. more ai on open source ai, did I prompt it to say this, maybe? #tokens distilled #smb ai #american big tech ai fever dream #snake river canyon jump #don't be evil knievil #the big short 2 #ipo #valuations #p/e ratios #weights are math #source:deepseek
    "
    Where does open source AI fall into place?

    Open-source AI is the escape hatch from the entire sovereignty vs. subsidy cage match.

    It makes your predicted "free trade zones" redundant, because the whole internet becomes a free trade zone.

    It undermines US big tech's valuation premium (good for competition, bad for investors).

    It partially neutralizes China's data-sovereignty advantage (if you run the model locally, you don't send them data).

    It cannot be stopped without breaking the internet or banning math.

    The only thing open-source can't solve is the compute gap for training the very largest models. So governments will fight over chips and training clusters, but they've already lost the battle over model distribution.

    That's the real shakeout: Closed-source frontier models as state assets, open-source everything else as a global commons."

  16. Storm-0558 hacks of Microsoft Exchange

    In mid-July 2023, Microsoft reported that a Chinese hacking group tracked as '#Storm0558' breached the email accounts of 25 organizations, including US and Western European government agencies, using #forged #authentication #tokens from a stolen Microsoft consumer #signing #key.

    Using this stolen key, the Chinese threat actors exploited a zero-day vulnerability in the #GetAccessTokenForResource API function for Outlook Web Access in Exchange Online (#OWA) to forge authorization tokens.

    These tokens allowed the threat actors to impersonate Azure accounts and access email accounts for numerous government agencies and organizations to monitor and steal email.

    After these attacks, Microsoft faced a lot of criticism for not providing adequate #logging to Microsoft customers for free. Instead, Microsft required customers to purchase additional licenses to obtain logging data that could have helped detect these attacks.

    After working with CISA to identify crucial logging data needed to #detect #attacks, Microsoft announced that they now offer it for free to all Microsoft customers.

    c.im/@cdarwin/1108682528634912

  17. Cointelegraph accelerator program welcomes Brickken: A new step in asset tokenization - By participating in Cointelegraph’s Accelerator Program, Brickken... - cointelegraph.com/news/cointel #cointelegraph #blockchain #business #tokens