CBF_Studio

PhD in Linguistics - Natural Language Interfaces #AI #VUI #CUI #Design - Then cities, life and culture within and beyond computational thinking

[CBF_Studio @CBF_Studio]

@futurism Andreessen explaining how AI will benefit humanity has the energy of a medieval priest trying to explain compound interest to peasants right before inventing debt slavery.
They clearly did not get enough Kool-Aid for a 3 hour long interview 🤣🤮

[CBF_Studio @CBF_Studio]

@futurism Andreessen explaining how AI will benefit humanity has the energy of a medieval priest trying to explain compound interest to peasants right before inventing debt slavery.
They clearly did not get enough Kool-Aid for a 3 hour long interview 🤣🤮

[Futurism @futurism]

"I mean, look, so it, it is, alright — I mean, alright I'm gonna give you the deepest of all pitches, I'm gonna give you the, the — okay." https://t.co/M3S01Qx8Qc

[Andrew Ng @AndrewYNg]

As amazing as LLMs are, improving their knowledge today involves a more piecemeal process than is widely appreciated. I’ve written before about how AI is amazing... but not that amazing. Well, it is also true that LLMs are general... but not that general. We shouldn’t buy into the inaccurate hype that LLMs are a path to AGI in just a few years, but we also shouldn’t buy into the opposite, also inaccurate hype that they are only demoware. Instead, I find it helpful to have a more precise understanding of the current path to building more intelligent models.

First, LLMs are indeed a more general form of intelligence than earlier generations of technology. This is why a single LLM can be applied to a wide range of tasks. The first wave of LLM technology accomplished this by training on the public web, which contains a lot of information about a wide range of topics. This made their knowledge far more general than earlier algorithms that were trained to carry out a single task such as predicting housing prices or playing a single game like chess or Go. However, they’re far less general than human abilities. For instance, after pretraining on the entire content of the public web, an LLM still struggles to adapt to write in certain styles that many editors would be able to, or use simple websites reliably.

After leveraging pretty much all the open information on the web, progress got harder. Today, if a frontier lab wants an LLM to do well on a specific task — such as code using a specific programming language, or say sensible things about a specific niche in, say, healthcare or finance — researchers might go through a laborious process of finding or generating lots of data for that domain and then preparing that data (cleaning low-quality text, deduplicating, paraphrasing, etc.) to create data to give an LLM that knowledge.

Or, to get a model to perform certain tasks, such as use a web browser, developers might go through an even more laborious process of creating many RL gyms (simulated environments) to let an algorithm repeatedly practice a narrow set of tasks.

A typical human, despite having seen vastly less text or practiced far less in computer-use training environments than today's frontier models, nonetheless can generalize to a far wider range of tasks than a frontier model. Humans might do this by taking advantage of continuous learning from feedback, or by having superior representations of non-text input (the way LLMs tokenize images still seems like a hack to me), and many other mechanisms that we do not yet understand.

Advancing frontier models today requires making a lot of manual decisions and taking a data-centric AI approach to engineering the data we use to train our models. Future breakthroughs might allow us to advance LLMs in a less piecemeal fashion than I describe here. But even if they don’t, the ongoing piecemeal improvements, coupled with the limited degree to which these models do generalize and exhibit “emergent behaviors,” will continue to drive rapid progress.

Either way, we should plan for many more years of hard work. A long, hard — and fun! — slog remains ahead to build more intelligent models.

[Original text: https://t.co/SHRN5JDvTW ]

[Quindici Zero 🎾 @quindicizero]

𝗜𝗥𝗥𝗘𝗔𝗟𝗘. 🛸

Jannik Sinner concede solo 3 game a Jiri Lehecka, superandolo con lo score di 6-0 6-1 6-2 nel terzo round a Parigi e conquistando la VITTORIA PIÙ NETTA della sua carriera a livello Slam: 17^ vittoria consecutiva a livello Slam, la 64^ di fila contro un giocatore fuori dalla top 20.

Raggiunge la seconda settimana di uno Slam per la 14^ volta negli ultimi 15 disputati.

SEMPLICEMENTE IN-CRE-DI-BI-LE!

[CBF_Studio @CBF_Studio]

@usopen @andreeva_mirra Congratulations to @andreeva_mirra and @conchitamartinz ! 🎉🎉🎉

[US Open Tennis @usopen]

THIS IS WHAT DREAMS ARE MADE OF. ✨

Madison Keys is the Australian Open Champion!

[US Open Tennis @usopen]

A mutual respect in Melbourne.

[US Open Tennis @usopen]

Two legends on the same side of the net 🤩

Hello, Andy and Novak!

[CBF_Studio @CBF_Studio]

@gdb Too funny! 🤣

[Melodies & Masterpieces @SVG__Collection]

Bill Evans - Very Early

There’s no better way to welcome the weekend than with Bill Evans…

[US Open Tennis @usopen]

Unas palabras de Delpo para Djoko 🥹

[Roger Federer @rogerfederer]

Vamos, @RafaelNadal!

As you get ready to graduate from tennis, I’ve got a few things to share before I maybe get emotional.

Let’s start with the obvious: you beat me—a lot. More than I managed to beat you. You challenged me in ways no one else could. On clay, it felt like I was stepping into your backyard, and you made me work harder than I ever thought I could just to hold my ground. You made me reimagine my game—even going so far as to change the size of my racquet head, hoping for any edge.

I’m not a very superstitious person, but you took it to the next level. Your whole process. All those rituals. Assembling your water bottles like toy soldiers in formation, fixing your hair, adjusting your underwear... All of it with the highest intensity. Secretly, I kind of loved the whole thing. Because it was so unique—it was so you.

And you know what, Rafa, you made me enjoy the game even more. 

OK, maybe not at first. After the 2004 Australian Open, I achieved the #1 ranking for the first time. I thought I was on top of the world. And I was—until two months later, when you walked on the court in Miami in your red sleeveless shirt, showing off those biceps, and you beat me convincingly. All that buzz I’d been hearing about you—about this amazing young player from Mallorca, a generational talent, probably going to win a major someday—it wasn’t just hype.

We were both at the start of our journey and it’s one we ended up taking together. Twenty years later, Rafa, I have to say: What an incredible run you’ve had. Including 14 French Opens—historic! You made Spain proud... you made the whole tennis world proud.

I keep thinking about the memories we’ve shared. Promoting the sport together. Playing that match on half-grass, half-clay. Breaking the all-time attendance record by playing in front of more than 50,000 fans in Cape Town, South Africa. Always cracking each other up. Wearing each other out on the court and then, sometimes, almost literally having to hold each other up during trophy ceremonies.

I’m still grateful you invited me to Mallorca to help launch the Rafa Nadal Academy in 2016. Actually, I kind of invited myself. I knew you were too polite to insist on me being there, but I didn’t want to miss it. You have always been a role model for kids around the world, and Mirka and I are so glad that our children have all trained at your academies. They had a blast and learned so much—like thousands of other young players. Although I always worried my kids would come home playing tennis as lefties.

And then there was London—the Laver Cup in 2022. My final match. It meant everything to me that you were there by my side—not as my rival but as my doubles partner. Sharing the court with you that night, and sharing those tears, will forever be one of the most special moments of my career.

Rafa, I know you’re focused on the last stretch of your epic career. We will talk when it’s done. For now, I just want to congratulate your family and team, who all played a massive role in your success. And I want you to know that your old friend is always cheering for you, and will be cheering just as loud for everything you do next.

Rafa that!

Best always, your fan, 

Roger

[Jannik Sinner @janniksin]

Good battle 👊🏼💪🏼 forza

[Iga Świątek @iga_swiatek]

Gratulacje @MFrech97 💪🏼👏🏼☺️

[Jannik Sinner @janniksin]

Benvenuti nella squadra Marco e Ulises 💪🏼

[Roland-Garros @rolandgarros]

The first Italian player in the Open Era to reach all Grand Slam R16 in a single calendar year 💫🇮🇹

#USOpen @JasminePaolini

[ATP Tour @atptour]

FORZA JANNIK 👏

Sinner is the first to qualify for this year’s Nitto ATP Finals, and is ready to battle it out on home soil 💪🇮🇹

@nittoatpfinals | #NittoATPFinals | @janniksin

[Jasmine Paolini @JasminePaolini]

Many fans want to take selfies with me and Sara! 🤣

(…gracias Carlos por la foto!)

[Wimbledon @Wimbledon]

A call so close, @BenShelton got the binoculars out 👀

#Wimbledon