I see

This is a very broad question but in general, yes.

On multiple occasions there such a big overlap between the fields that unless someone is doing some highly specialised (e.g. some very particular problems in Measure Theory or Computer Vision) the underlying skills will be transferable and almost interchangeable (e.g. in Gaussian Processes- or Causality- related topics).

Basically, current trends just ignore any reasonable thing, such as train/valid/test set. For now, the bigger, the better. This requires quite a lot of tech support functions (parallelization and data pipelining in particular) rather than theory-related ones.

Are any benchmark scores such as MMLU or BigBench available for Aleph Alpha's models?

Could you elaborate

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>the fact that they invented it, but didn't release it, it means that they thought the technology would be a threat to them

I slightly disagree with this.

Imo, from what I know of Google from people that do or used to work there - they likely didn't care or didn't think of it.

Inside Google is a researcher's playground and there's little to no pressure to ever go to market. I've seen things that are extremely impressive that's never been published or put into a product. Asking why - they just don't care to do so.

The higher-ups lack imagination now, and unless something can directly obviously improve ads, they don't care.

So for years you've had engineers not caring to make something marketable, and leadership not caring but still throwing money at it. My impression is that leadership was looking for something that was so obviously a home run they didn't want to bother with releasing and iterating.

In terms of Consumer Apps, the Poe app from Quora has access to two models from Open AI and one from Anthropic.

Perplexity.ai, YouChat and Neeva are search engines that integrated LLMs.

Google has an AI + Search Event on Wednesday where they are likely to announce something as well.

In terms of APIs and getting a feeling for these models, I would use OpenAI's APIs. Their models are the best publically available models. Open Source models are still far behind.

This is all about timing. Currently stats/maths capabilities are not are their best.

>and it’s naïve for people to think ChatGPT is so special that it’s a threat to Google.

Google does a ton of R&D but really sucks(or doesn't care) about productizing.

That's where the real "threat" to them lies.

There are a lot of people with absolutely no disposable income. Just having to move is a huge financial stress to them. Aside from the actual cost of moving, you might need to spend more time commuting which adds more cost. A ton of people are very vulnerable financially. Why do you think there are so many homeless people? They’re just lazy? I’m curious where you live? This stuff is really obvious

have you tried murf.ai and wellsaid labs?

Yes, it is useful. The breakdown between PhD types would depend on the specific needs of the hiring organization.

RWKV 14B, trained on The Pile.

Only if you want to build AI with quantuum processors

I much prefer to see the tokens as they are generated, it's much better UX as you can abort the generation if you feel it's not going in the right direction. All my GPT3 integrations use stream:true and display every word as it comes in.

I think populism in EU reached it’s climax before covid. Now with the energy crisis in EU, people are starting to realize governments suck and they need to start relying a bit more on local corporations

Populism is on the rise in Europe.

This isn't true - GDPR puts much more onerous restrictions on what consent must be gained before personal data is processed. Much of what cookies collect is considered personal data, and so immediately on GDPR's passing, many websites started to change their cookie acceptance boxes to these massive things which take up half the screen and have granular consent check boxes. Another factor which just makes browsing the web increasingly inconvenient for the average user.

Make no mistake - there is no TTS more humanlike than Azure ATM, but the exact voice was likely fiddled around with a bit to get the exact pronunciation, or ran through a filter.

2 days ago I was comparing all the state-of-the-art TTS', and while Google's Neural2 came close to the video, it does not feature similar voices to the one in the video.

i gave it a look but the one in the video seems more proffesional, human-like almost so its not azure

Sorry, my library seems a bit outdated on that side.

But the one from Wikipedia looks great at first sight. Ralph., Kimball (2004). The data warehouse ETL toolkit : practical techniques for extracting, cleaning, conforming, and delivering data

I would start with learning programming very well. On the side you can learn necessary math on school and from youtube. For calculus i recommend professor Leonard. If you dont have good foundations he start from i guess literally adding numbers. You will need good software skills anyways and you can do it without math. Create a website to show your future projects. Solve some programming problems in codewars etc. Programming language is not that important you just need to get used to abstract thinking. You can embed some AI models from OpenAI etc. to your website with their public API's.

When you know enough calculus, you can dive into ML theory with good skills in your belt. Eventually you can implement research papers and become a research engineer to work on cutting edge development in ML world. When you know some calculus i suggest you to watch Tesla AI ex-Lead Engineer Andrej Karpathy's lectures, he also briefly mentions relevant calculus. Before Karpathy i recommend you neural nets from scratch series in youtube.

Agreed, but they are forced to play catch up now, and not sure if they are ready. It's not just about the pure tech, it's about the UX, the scalability, the liability, etc. It's safe to say Bing has worked on this before ChatGPT went public, so several months already. Also, OpenAI uses Azure, so they know exactly the loads and plan to scale. The fact that they have way less users currently helps as well.

GLM-130b https://huggingface.co/spaces/THUDM/GLM-130B

Cohere's models https://cohere.ai/

Aleph Alpha's models https://app.aleph-alpha.com/

AI21's models https://www.google.com/url?sa=t&source=web&rct=j&url=https://studio.ai21.com/&ved=2ahUKEwigktrH-_78AhWAFlkFHefHC3IQFnoECAsQAQ&usg=AOvVaw1L0TKoIvBtSFFB1oJsG5nW