Dan O’Brien @danOBtech

@danielnewmanUV Go team Futurum! Awesome for you to be part of this important ecosystem wide effort to drive continued semiconductor innovation, led by @Applied4Tech $AMAT

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Dan O’Brien @danOBtech

a week ago

@GavinSBaker @TheFuturumGroup And to the point on Ai infra impact...

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Dan O’Brien @danOBtech

a week ago

@GavinSBaker Open-weight AI adoption has made material progress in our ETR community survey of enteprise decision makers. @TheFuturumGroup

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Dan O’Brien @danOBtech

a week ago

Very interesting move, labor shakeup in the GSI space

unusual_whales @unusual_whales

a week ago

BREAKING: The Labor Department has suspended 8 major tech and outsourcing firms from the PERM program, the first step toward sponsoring foreign workers for green cards. The government will no longer accept new or process pending PERM applications from: Cognizant Infosys

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Dan O’Brien @danOBtech

2 weeks ago

@damnang2 You need a team to support you!

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Dan O’Brien @danOBtech

2 weeks ago

Timely, model routing

Elon Musk @elonmusk

2 weeks ago

Important note regarding Grok @bot: Going forward, @SpaceX will use the best back end model for any given task, including Claude Opus 5.5, MidJourney, Suno and other leading APIs. Whatever is most likely to give you the best outcome.

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Dan O’Brien @danOBtech

2 weeks ago

Model routing, the systematic way of most efficiently matching model to task, is the path to driving AI ROI, by aligning inference cost to outcome value. Token caps are the short term answer, but model to task matching is the long term answer. Only a few vendors have the potential to solve this at the platform level and it will be an interesting battle ground to watch. This isn’t dissimilar to the challenge enterprise technology leaders faced over the past decade, matching their workloads most efficiently to infrastructure across their hybrid, multi-cloud estates. I’m excited about what @Signal_65 is doing with PINNACLE, because the data is being created to help tackle this problem at scale. @ETRnews @TheFuturumGroup

ETR @ETRnews

2 weeks ago

59% of enterprises building AI apps now cap token usage to control inference costs. In March it was 50%. No other cost-control method grew faster. Data: ETR, a Futurum Group company

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Dan O’Brien @danOBtech

2 weeks ago

@TheFuturumGroup 🚀

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The Futurum Group @TheFuturumGroup

2 weeks ago

The challenge for technology companies is not a shortage of channels, content or campaigns. It is making every part of the GTM motion work together. As pipeline expectations increase and buying journeys become more complex, fragmented execution creates friction between the story a company tells, the audiences it reaches and the demand it generates. 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗶𝗻𝗴 𝗙𝘂𝘁𝘂𝗿𝘂𝗺 𝗠𝗲𝗱𝗶𝗮, 𝗚𝗧𝗠 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝗯𝘂𝗶𝗹𝘁 𝗳𝗼𝗿 𝘁𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀. It brings together four connected capabilities designed to carry that motion from attention to action: 🔹 𝗖𝗥𝗘𝗔𝗧𝗘 stories that matter. 🔹 𝗥𝗘𝗔𝗖𝗛 the right people. 🔹 𝗘𝗡𝗚𝗔𝗚𝗘 with credibility that sticks. 🔹 𝗔𝗖𝗧𝗜𝗩𝗔𝗧𝗘 demand you can act on. Each capability has a role. Together, they create continuity from attention and visibility to trust and impact. The result is a more connected approach to GTM execution, with each capability supporting what comes next. Explore Futurum Media: futurumgroup.com/media #FuturumMedia #GTM #B2BMarketing

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AMD @AMD

3 weeks ago

More users shouldn't have to mean slower AI. In @Signal_65 RAG testing hosted via @tensorwave, AMD Instinct MI355X delivered ~42% lower p99 latency and roughly 2x the concurrent-user headroom before breaching the evaluated SLA: bit.ly/45hAvl3

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Dan O’Brien @danOBtech

3 weeks ago

@TheSixFiveMedia @PatrickMoorhead Accurate, market is underestimating Terafab momentum

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Dan O’Brien @danOBtech

3 weeks ago

Pay attention to what @Signal_65 has been working on, the team is bringing a new and very pragmatic view to model and agent evaluation. Net - it’s all about user outcome economics. There is also a neutrality and transparency here that is sorely lacking in other evals

Ryan Shrout @ryanshrout

3 weeks ago

The interesting traits we find with these different models and design principles continues to open my eyes. It's clear @OpenAI uses a strategy to scale model intelligence based on token consumption, allowing them to move up and down our @Signal_65 PINNACLE benchmark and giving

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Dan O’Brien @danOBtech

3 weeks ago

@danielnewmanUV Obvious op

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Dan O’Brien @danOBtech

3 weeks ago

@PatrickMoorhead 💪🏼

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Signal65 @Signal_65

4 weeks ago

Any enterprise working on @AnthropicAI Claude Opus for agent work gets more of the work done for less money by moving to yesterday's brand-new Opus 5.5, and in our testing the gap is...pretty large. Opus 5.5 gets more work done for more people, at a noticeably lower price than Anthropic offered before, as measured by @Signal_65 PINNACLE. ➡️ 2.3x fewer weighted errors than Claude Opus 5, and 100% of the multi-step jobs finished end to end against 95% ➡️ 34% less per correct task (!!), $0.40 against $0.60, on a list price 20% below Opus 5 with cache reads at 5% of input rather than 10% ➡️ Fabrication in retrieval answers down from 7.6% to 2.8% ➡️ It also passes Claude Fable 5.1 with 1.3x fewer weighted errors at 63% less per correct task Full comparison on the Signal65 PINNACLE results views at pinnacle.signal65.com