This may not be the actual reason in this case, but I think it's good to be aware of: A non-zero chunk of "ai for science" research done at tech companies is basically done for marketing. Even in cases where it's not directly beneficial for the companies products or is unlikely to really lead to anything substantial, it is still good for "prestige"
Local inference. I imagine they have an interest in making this and other cutting edge models small enough to be possible to do quick inference on their desktop machines. The article shows that, with Figure 1E demonstrating inference on an M2 Max 64 GB.
Frankly, it's a great idea. If you are a small pharma company, being able to do quick local inference removes lots of barriers and gatekeeping. You can even afford to do some Bayesian optimization or RL with lab feedback on some generated sequences.
In comparison, running AlphaFold requires significant resources. And IMHO, their usage of multiple alignments is a bit hacky, makes performance worse on proteins without close homologs, and requires tons of preprocessing.
A few years back, ESM from Meta already demonstrated that alignment-free approaches are possible and perform well. AlphaFold has no secret sauce, it's just a seq2seq problem, and many different approaches work well, including attention-free SSMs.
I think people often interpret a bit too much.
Perhaps it’s just some researchers who got enough freedom to run and publish interesting work within apple. For a company like apple it makes sense to have a research lab with considerable freedoms even if protein folding is not a core interest, which is why you see it published but not the formula for the new Corning Gorilla glass…
Will be fascinating to see how the market breaks down in the future, will enough people want a third best model they can run on prem, or will people all be fighting in line for the top models that are a few cents more per token on supercomputers.
To sell computers? 20 years ago, Apple had scientific poster sessions at WWDC and worked to bring PyMol to the Mac. The pictures of proteins you see in the paper were generated with PyMol as are probably >50% of the protein images in scientific papers for the last 15 years.
If Warren Delano (the author of PyMol) were still with us, I think he would be amazed at where we are now with AlphaFold, and all the rest. At least what he hoped for, that software like this would be open source and peer-reviewable, has mostly held true.
They have a much better reputation that most companies. I think they're doing okay compared to google, facebook, oracle, etc. Few people are going to think a corp is "doing good" but reputation does still matter somewhat.
You're confusing your opinion of the company with the perception by the general public. Apple's definitely not perceived as 'an office appliance company' by your average person. It's considered a high-end luxury brand by many[1].
I think their public sales data shows Apple sells mainly to consumers, and mainly iPhones at that.
Like 1980s SONY, they are the top of the line consumer electronics giant of the time. The iPhone is even more successful than the Walkman or Trinitron TVs.
They also sell the most popular laptops,to consumers as well as corporate. Like SONY’s VAIO but more popular again.
Ah, I see where we went wrong here, you never specified that you meant reputation in your mind only. FYI, “reputation” is usually considered to be related to a general public opinion, not your personal one.
