NPPS Leadership Team

[Anže Slosar <anze AT bnl.gov>]

Hi all,

So let me add to this thread that regardless of the fact that they were
given as boundary conditions, I share many of Brett's concerns.

off the recrod: after working with supposed "AI/ML" experts on the
SciDac project for the past 4 years I am underwhelmed. The two main
issues are:

- they do not seem to be cutting edge in the sense google and facebook
  are. What they do in practice is to play with the box of lego bricks
  provided by the industry giants who seem to have the real brains
  working on this. But they are not either capable or willing to design
  special bricks that we would need.

- because giants are interested recognizing cats and dogs rather than
  careful propagation of noise, we end up cats and dogs. The real
  problem is that it is easy to train network to produce something that
  is much more impressively correct by eye than a simple old school
  method. But it is very difficult to ascertain noise properties and
  subtle biases from imperfect training datasets. Which makes these
  methods often borderline useless.

We need to find a constructive way of engaging with these people and
educating them about our needs rather than letting them apply
variational encoders and GANs to everything that moves.

        Anže


> Date: 2021-01-25T16:26:16-0500
> From: Brett Viren <bv AT bnl.gov>
> Subject: Re: [Phys-npps-mgmt-l] One slide presentation at the next Monday 
> 4pm meeting
> 
> Hi Elke,
>
> Aschenauer Elke-Caroline <elke AT bnl.gov> writes:
>
>> I’m must admit lost with your comments are you referring to what Torre 
>> added
>> on HEP or are you unhappy about the entire document or something else.
>
> Oh heck!  Okay, well I feel super chagrinned now.  I thought there are
> only two pages in the document so my knee jerk was only about the first
> "vision".  Sorry for my overreaction!
>
> After actually scrolling down, the EIC and HEP visions are much more
> lined up with my hopes for AI/ML at BNL.
>
> -Brett.