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Skyfire
Official website of the revolutionary new predictor of fiery sunrises and
sunsets using real meteorology data.
clouds  sky  mapping  colour  sunset  sunrise  photography  prediction  geography 
19 hours ago by robhawkes
MutationTaster
Unfortunately not. Unlike SIFT or PolyPhen which handle only single amino acid substitutions, MutationTaster works on DNA level and allows insertions and deletions. The exome alone comprises about 30 Mb with 3 possible single base exchanges at each site (let alone introns and InDels). These 30 M x 3 SBEs may affect several different transcripts, leading to about 30,000,000 (Mb) x 3 (SBEs) x 5 (transcripts) = 450,000,000 values to pre-compute.
We could of course generate such a list, but it would still not include the InDels and most of the introns. What is more important: such a list would take a very long time to generate and might soon become outdated. We rather spend our efforts on improving MutationTaster!
genomics  prediction  mutations  Sequence  Bioinformatics 
2 days ago by ccorbi
Superintelligence Risk Project Update II
https://www.jefftk.com/p/superintelligence-risk-project-update

https://www.jefftk.com/p/conversation-with-michael-littman
For example, I asked him what he thought of the idea that to we could get AGI with current techniques, primarily deep neural nets and reinforcement learning, without learning anything new about how intelligence works or how to implement it ("Prosaic AGI" [1]). He didn't think this was possible, and believes there are deep conceptual issues we still need to get a handle on. He's also less impressed with deep learning than he was before he started working in it: in his experience it's a much more brittle technology than he had been expecting. Specifically, when trying to replicate results, he's often found that they depend on a bunch of parameters being in just the right range, and without that the systems don't perform nearly as well.

The bottom line, to him, was that since we are still many breakthroughs away from getting to AGI, we can't productively work on reducing superintelligence risk now.

He told me that he worries that the AI risk community is not solving real problems: they're making deductions and inferences that are self-consistent but not being tested or verified in the world. Since we can't tell if that's progress, it probably isn't. I asked if he was referring to MIRI's work here, and he said their work was an example of the kind of approach he's skeptical about, though he wasn't trying to single them out. [2]

https://www.jefftk.com/p/conversation-with-an-ai-researcher
Earlier this week I had a conversation with an AI researcher [1] at one of the main industry labs as part of my project of assessing superintelligence risk. Here's what I got from them:

They see progress in ML as almost entirely constrained by hardware and data, to the point that if today's hardware and data had existed in the mid 1950s researchers would have gotten to approximately our current state within ten to twenty years. They gave the example of backprop: we saw how to train multi-layer neural nets decades before we had the computing power to actually train these nets to do useful things.

Similarly, people talk about AlphaGo as a big jump, where Go went from being "ten years away" to "done" within a couple years, but they said it wasn't like that. If Go work had stayed in academia, with academia-level budgets and resources, it probably would have taken nearly that long. What changed was a company seeing promising results, realizing what could be done, and putting way more engineers and hardware on the project than anyone had previously done. AlphaGo couldn't have happened earlier because the hardware wasn't there yet, and was only able to be brought forward by massive application of resources.
ratty  core-rats  ai  risk  ai-control  prediction  expert  machine-learning  deep-learning  speedometer  links  research  research-program  frontier  multi  interview  deepgoog  games  hardware  performance  roots  impetus  chart  big-picture  state-of-art  reinforcement  futurism  🤖  🖥 
2 days ago by nhaliday
Brexit: the day the whistling ended
There will be attempts by ministers and their supporters at avoidance, evasion and diversion. There will be name-calling and strident demands for patriotism. There will be blame-mongering and jockeying for succession. But what there will not be is any relevant minister taking this as seriously as the EU is doing.
brexit  prediction  ft 
11 days ago by Ciudilo

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