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submitted by /u/Denicce01 [link] [comments]

A year ago, most discussions were about which model was smartest. Now it increasingly feels like the bigger differentiators are becoming: latency orchestration context handling reliability inference economics developer workflow deployment flexibility The interesting shift is that model quality is improving across the board fast enough that “best benchmark” doesn’t automatically translate into “best real-world experience” anymore. We’re seeing more teams optimize around: workload routing hybrid local/cloud setups smaller specialized models faster iteration cycles predictable scaling costs In a weird way, AI feels like it’s maturing into a systems/infrastructure problem almost as much as a model problem. Curious if others are seeing the same shift or if frontier model capability still do...

What is the “personality” of an LLM? What actually differentiates models psychometrically? Since LLMs entered public use, researchers have been giving them psychometric questionnaires, with mixed results. Their answers often do not seem to reflect the same psychological constructs these tests measure in humans. So we asked a slightly different question: What do LLM responses to psychometric questionnaires actually reflect? We analyzed responses to 45 validated psychometric questionnaires completed by 50 different LLMs. The strongest source of variation was whether a model endorsed items about inner experience: emotions, sensations, thoughts, imagery, empathy, and other forms of first-person experience. We call this factor the Pinocchio Dimension. Importantly, the Pinocchio Dimension is not...

submitted by /u/andix3 [link] [comments]

I’m basically a total beginner when it comes to finance and economics maybe 2 or 3 months ago, and honestly trying to learn from reports or books used to completely destroy me. Too many charts, numbers, random terms I have to Google every 2 minutes. And I started using AI Podcast to kind of brute force my way into learning this stuff, and I’m honestly surprised by how much it helped. Instead of sitting there suffering through a 70-page report, I can turn it into conversational audio and just listen while driving or walking around. But those tools actually feel slightly different. Like NotebookLM feels more “AI teacher explains the document to you.” It’s really good at organizing information and walking through the important points clearly. And I enjoy Genspark AI Pods more because it feel...

Anthropic just partnered with SpaceX and doubled Claude Code rate limits effective today Big news dropped this morning. Anthropic signed a deal to use all compute capacity at SpaceX's Colossus 1 data center. That's 300+ megawatts and over 220,000 NVIDIA GPUs coming online within the month. But the part that actually matters to developers right now: What changed today: - Claude Code 5-hour rate limits are doubled (Pro, Max, Team, Enterprise) - Peak hours limit reduction on Claude Code is removed for Pro and Max - API rate limits for Claude Opus models raised considerably This is on top of their existing compute deals 5 GW with Amazon, 5 GW with Google/Broadcom, $30B of Azure capacity with Microsoft and NVIDIA, and $50B in infrastructure with Fluidstack. They also mentioned interest in devel...

One speaker (a VC) said his number for evaluating AI-native startups is ARR per engineer, and that the number ought to be going up. Almost every talk and every booth at the AI Agents Conference was selling a fix for something that broke this year when agents hit production. Observability, governance, supervisor agents, data substrates, "someone's gotta babysit the bots." But what's actually still going to be around in a couple years? What's defensible and durable? The old SaaS pitch was simple. We bundle the expensive engineering investments and domain expertise into a tool. You'd pay for the tool and generate outcomes, but it would be rare for the software company to have real alignment to the actual value created from those outcomes. That's breaking from two ends at once. In the direct...

submitted by /u/sksarkpoes3 [link] [comments]

submitted by /u/Professional-Web954 [link] [comments]