Perhaps your content quality meter needs a recalibration?
How so? What makes this blog stand out in terms of quality? I prefer a constructive discussion over personal questions, maybe you should, too.
Readit NewsSerious question: Why does it appear that pages from this URL very often end up on top of HN? I don't find the content particularly special compared to the average HN post. Does the algorithm prefer certain URLs?
I wish they'd open-source what they're shuttering. Would be a win-win as far as I can tell.
How is it a win for Google to release something open-source that had potentially cost them lots of money? Even if they don't need and pursue it anymore, why would they just give it to the competition?
It's always easily said to "just open-source" it but Google is a business and owes outside software developers nothing.
Mistral really became what all the other over-hyped EU AI start-ups / collectives (Stability, Eleuther, Aleph Alpha, Nyonic, possibly Black Forest Labs, government-funded collaborations, ...) failed to achieve, although many of them existed way before Mistral. Congrats to them, great work.
beernet commented on EU to ban anonymous crypto accounts and privacy coins by 2027 cointelegraph.com/news/eu... · Posted by u/alexey-salmin
The cost for a Bitcoin transaction today is $0.96.
The lowest daily average cost per transaction in the last month was $0.81, and the highest was $2.52.
Which is still quite a lot. Litecoin (among other alternatives) provides the exact same service for close to zero cost and at a better speed.
Call it AI, ML, Data Mining, it does not matter. Truth is these tools have been disrupting the SWE market and will continue to do so. People working with it will simply be more effective. Until even them are obsolete. Don't hate the player, hate the game.
Tangential, but this brings up a really interesting question for me.
LLMs are multi-lingual without really trying assuming the languages in question are sufficiently well-represented in their training corpus.
I presume their ability to translate comes from the fact that there are lots of human-translated passages in their corpus; the same work in multiple languages, which lets them figure out the necessary mappings between semantic points (words.)
But I wonder about the translation capability of a model trained on multiple languages but with completely disjoint documents (no documents that were translations of another, no dictionaries, etc).
Could the emerging latent "concept space" of two completely different human languages be similar enough that the model could translate well, even without ever seeing examples of how a multilingual human would do a translation?
I don't have a strong intuition here but it seems plausible. And if so, that's remarkable because that's basically a science-fiction babelfish or universal translator.
My hunch is it would work somewhat, but poorly.
Languages encode similar human experiences, so their conceptual spaces probably have natural alignments even without translation examples. Words for common objects or emotions might cluster similarly.
But without seeing actual translations, a model would miss nuances, idioms, and how languages carve up meaning differently. It might grasp that "dog" and "perro" relate to similar concepts without knowing they're direct translations.
Is this a serious comment? "Apple has the means to do something highly illegal that benefits them and they're stupid they don't make use of it?"
Even if you were right (which I don't think) this is not how one should do or think about business.
Still, funny to see numerous hyped GenAI start-ups with bad monetary traction jump on the bandwagon and proclaim MCP as the latest revolution (after RAG, Agents, you name it)...All of these are simply tools which add zero value by themselves. Looking forward to the VC wake up calls.