Dan O’Brien @danOBtech

@damnang2 You need a team to support you!

Timely, model routing

Elon Musk @elonmusk

23 hours 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.

7K 8K 103K 75.3M 10K

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

17 hours 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

1 0 7 5K 3

@TheFuturumGroup 🚀

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

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

@TheSixFiveMedia @PatrickMoorhead Accurate, market is underestimating Terafab momentum

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

2 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

0 0 4 1K 0

@danielnewmanUV Obvious op

@PatrickMoorhead 💪🏼

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

@danielnewmanUV Bullish

@StockSavvyShay Big friction between cross-platform agents and native platform agents, most companies want to own the experience of their own platform, but most consumers want cross-platform

@damnang2 I know someone who could help

@danielnewmanUV There is so much talent here on X, I would love to help a few folks turn their passion or hobby into a lucrative career.

Limited seats available on this 🚀 If you want to work with the best clients in the world, at the edge of technology innovation, with the best data & platform to elevate your research, and have fun collaborating with a smart, driven group of people, then let’s talk! [email protected]

Daniel Newman @danielnewmanUV

2 weeks ago

Some of our best recent hires have been found here on X. So I’m going back to the well here. We are hiring Tech Analysts at Futurum. Looking for AI-pilled, tech-obsessed, data-loving, social media crazed analysts across Semiconductors, Infrastructure, Cyber, Developer/DevOps,

18 15 81 17K 9

The industry spent this week debating the AI pacing argument Anthropic CEO Dario Amodei set off with "We Must Pace the Frontier." We asked 50 large-enterprise buyers from our ETR Community: 70% say the labs should slow down, but only 20% read lab-proposed slowdowns as genuine safety measures. The detail that makes this worth publishing sits in a question nobody would think to look at. Among the 72% who want more regulation, 86% cite safety and misuse risk, but only one respondent cited slowing the pace so their own organization could keep up.

See the full study at the link below. The Futurum Intelligence Platform offers this type of timely, proprietary insight every day. info.futurumgroup.com/ai-pacing-flas…

There’s been a lot of talk this week about slowing down or pacing AI development. A lot has been said from top leaders across the industry, government officials, and in the media. At @TheFuturumGroup we felt that the buyer and user were underrepresented in this industry dialogue, so we talked to 50 large US enterprise technology leaders from our @ETRnews community to see how the biggest AI consumers and spenders feel about the pacing debate. Key findings include: 1: the argument lands. 70% said the labs should slow down. 2: the messenger doesn't. Only 20% read lab-proposed slowdowns as genuine safety measures. 46% read them as competitive positioning. Buyers accept the argument and distrust the arguer. 3: they converge on a mechanism that neither the labs nor governments control. Independent third-party evaluation was the top answer for who should set the pace, at 40%. And it moves every commercial metric we tested — 70% more willing to deploy in production, 74% more confident building on that lab's models, 60% would pay a premium for independently certified models. Demand for third-party certification isn't a preference. It's a capability gap. Whoever builds the assurance layer for frontier models has a market waiting.

@kellangrenier I’m a sucker for a well placed Bretton Woods reference…