I have to imagine governments are closely monitoring prediction markets as part of their intelligence apparatus. But then you just add another layer of subterfuge. Imagine a D-Day prediction market... "Will the Allies Land in Normandy, Pas-de-Calais, or somewhere else?" The US might buy a major position on Pas-de-Calais the night before as a decoy!
Readit Newsalach11 commented on A prediction market user made $436k betting on Maduro's downfall bbc.com/news/articles/cx2... · Posted by u/tartoran
alach11 commented on Gemini 3 Flash: Frontier intelligence built for speed blog.google/products/gemi... · Posted by u/meetpateltech
I really wish these models were available via AWS or Azure. I understand strategically that this might not make sense for Google, but at a non-software-focused F500 company it would sure make it a lot easier to use Gemini.
Agreed. There is no "beginner" or amateur programmer who could complete even part of a single Advent of Code problem.
Usually the first day or two are readily solvable in Excel with just regular spreadsheet formulas.
> Pricing is now $5/$25 per million [input/output] tokens
So it’s 1/3 the price of Opus 4.1…
> [..] matches Sonnet 4.5’s best score on SWE-bench Verified, but uses 76% fewer output tokens
…and potentially uses a lot less tokens?
Excited to stress test this in Claude Code, looks like a great model on paper!
This is the biggest news of the announcement. Prior Opus models were strong, but the cost was a big limiter of usage. This price point still makes it a "premium" option, but isn't prohibitive.
Also increasingly it's becoming important to look at token usage rather than just token cost. They say Opus 4.5 (with high reasoning) used 50% fewer tokens than Sonnet 4.5. So you get a higher score on SWE-bench verified, you pay more per token, but you use fewer tokens and overall pay less!
alach11 commented on Olmo 3: Charting a path through the model flow to lead open-source AI allenai.org/blog/olmo3... · Posted by u/mseri
I'm just now moving my main workflows off openai over to local models and I'm starting to find that these smaller models main failure mode is that they will accept edgecases with the goal of being helpful.
Especially in extraction tasks. This appears as inventing data or rationalizing around clear roadblocks.
My biggest hack so far is giving them an out named "edge_case" and telling them it is REALLY helpful if they identify edgecases. Simply renaming "fail_closed" or "dead_end" options to "edge_case" with helpful wording causes qwen models to adhere to their prompting more.
It feels like there are 100s of these small hacks that people have to have discovered... why isn't there a centralized place where people are recording these learnings?
Just curious - are you using Open WebUI or Librechat as a local frontend or are all your workflows just calling the models directly without UI?
This is a really impressive release. It's probably the biggest lead we've seen from a model since the release of GPT-4. Seems likely that OpenAI rushed out GPT-5.1 to beat the Gemini 3 release, knowing that their model would underperform it.
I don’t think these agents are doing anything a dedicated human couldn’t do, only enabling it at scale. Relying on “not being one of few they focus on” as security is just security as obscurity. You were living on borrowed time anyway.
"Quantity has a quality all its own". It's categorically different to be able to do harm cheaply at scale vs. doing it at great cost/effort.
alach11 commented on You should write an agent fly.io/blog/everyone-writ... · Posted by u/tabletcorry
So AI companies are profitable when you ignore some of the things they have to spend money on to operate?
Snark aside, inference is still being done at a loss. Anthropic, the most profitable AI vendor, is operating at a roughly -140% margin. xAI is the worst at somewhere around -3,600% margin.
Can you cite your source for inference being at a loss? This disagrees with most of what I've read.
But posting something positive and getting slammed in the comments? That's depressing. So the barrier to posting something positive seems higher.
https://www.sciencedirect.com/science/article/abs/pii/002210...