Plenty of pretty block diagrams and high-level overview are available online, but little (or nothing) can be found on real use of the framework and its benefits.

I had an idea a long time ago that would allow us to make “soft AGI” by making models into “nodes” that would have an input and output representations and routing them to achieve the task needed.

Basically a “marketplace” of models that would have the metadata to be easily searchable and standardized types/representations that would allow them to link seamlessly. We could then build a system that would get a text query and phone sensors as input and would determine input-output representations for the query. The system would then find a route (ideally using the most cost-efficient path, nodes being rated with a compute cost) to achieve the task.

Is Google trying to make this with MediaPipe?

I think once it is ou of beta they will open a repository for our “Calculators” (as they call nodes) to make this happen. They could maybe provide cheap or free execution on Google Cloud but use the data passing through as training material. The thing is we could make models more modular and reuse pretrained nodes already on the system. It would make training really fast as most of the model is already pretrained and avoid overfitting because the nodes are used for other tasks as well.

What do you think of it?

An idea that I’ve had for a year or two now and recently started on it. It’s meant to easily share datasets as compiling data is backbreaking work, so that others do not have to undergo the same experience. It’s still in early stage.

Github link: https://github.com/ezhou7/repm

Just received the email:

“””

We are pleased to announce the opening of Registration for NeurIPS 2019:

Register:

Check pricing here. Registration opens Sept 6th at 8 a.m. Pacific. Please see below for more information about our new lottery registration system.

What’s new in 2019:

• The old first-come-first-served registration has been replaced with a lottery. It is no longer necessary register in the first few minutes after registration opens. Add yourself to the lottery between Sept 6th and Sept 20th for a chance to be randomly chosen to register. Click the green “Register Starting Sept 6th” button on the home page after registration opens for more inforrmation. If you are in an Asian, African or Middle Eastern timezone, there is no longer a need to wake up in the night to register. Take your time; it won’t hurt your chances of getting a ticket.
• NeurIPS 2019 will be held at the Vancouver Convention Center, Vancouver CANADA Sun Dec 8th through Sat the 14th. The check-in desk opens Sunday morning at 8:00 am in the West building of the VCC.
• Students must upload a scan of their student IDs to qualify for student pricing and financial support. Students must present their valid student ID at the check-in desk to pick up their badge.
• The entire meeting will be live-streamed.

“””

Thoughts? Seems like this may increase the pool of competing attendees as a side effect due to the time barrier removal. Any way to roughly estimate the % chance of getting a ticket?

In my opinion the two main contributors will be NLP and Reinforcement Learning. I also think Self-Supervised Learning is going to have a big role. What’s your opinion?

I’ve seen a few posts on this subreddit and /r/learnmachinelearning asking how to finetune GPT-2 and generate text from it. As the creator of gpt-2-simple, I’ve had a lot of experience working with GPT-2, so here’s a (lengthy!) blog post on how to finetune GPT-2 and generate text using gpt-2-simple, along with a history of GPT-2 finetuning and its future:

https://minimaxir.com/2019/09/howto-gpt2/

Let me know if you have any questions!

I submitted the abstract for AAAI 2020, roughly 3 days before the final deadline. One of my colleagues did the same 2 days before me, and got a submission number less than 100. I got a submission number higher than 4k. Now I’m reading on Twitter that they got more than 10k submissions.

Now, I also believe they are going to have several issues with the reviewers, as they’re asking reviewers to review 5 to 10 papers, with no chance of load reduction. It is my understanding that many people are simply bailing out, for obvious reasons.

What you your experience so far? Are you still submitting the final paper, or may decide to submit somewhere else? I was considering submitting my work to IAAI instead, which is more application focused and is not on the way to implode as AAAI.