m15i

https://archive.md/PvbqA

The Prologue to Bertrand Russell's Autobiography

What I Have Lived For

Three passions, simple but overwhelmingly strong, have governed my life: the longing for love, the search for knowledge, and unbearable pity for the suffering of mankind. These passions, like great winds, have blown me hither and thither, in a wayward course, over a great ocean of anguish, reaching to the very verge of despair. I have sought love, first, because it brings ecstasy - ecstasy so great that I would often have sacrificed all the rest of life for a few hours of this joy. I have sought it, next, because it relieves loneliness--that terrible loneliness in which one shivering consciousness looks over the rim of the world into the cold unfathomable lifeless abyss. I have sought it finally, because in the union of love I have seen, in a mystic miniature, the prefiguring vision of the heaven that saints and poets have imagined. This is what I sought, and though it might seem too good for human life, this is what--at last--I have found.

With equal passion I have sought knowledge. I have wished to understand the hearts of men. I have wished to know why the stars shine. And I have tried to apprehend the Pythagorean power by which number holds sway above the flux. A little of this, but not much, I have achieved.

Love and knowledge, so far as they were possible, led upward toward the heavens. But always pity brought me back to earth. Echoes of cries of pain reverberate in my heart. Children in famine, victims tortured by oppressors, helpless old people a burden to their sons, and the whole world of loneliness, poverty, and pain make a mockery of what human life should be. I long to alleviate this evil, but I cannot, and I too suffer.

This has been my life. I have found it worth living, and would gladly live it again if the chance were offered me.

how does antibiotic medication affect our gut microbiota generally, and our alzheimer’s disease risk specifically?

https://archive.md/zChiM

https://archive.md/fXRWr

https://archive.ph/kQVpU

Regarding training ResNet50, even though img/sec is less than the 3090, could a 64gb m1 max accommodate larger image sizes than the 24gb 3090?

Good points. I look forward to some benchmarks. Just hoping for an alternative to Nvidia sooner than later. Dreaming apple will solve it and offer a 1.5 TB mac pro.

It’s all about the RAM. 64GB would allow input of larger image sizes and/or nets with more parameters. Right now, the consumer card with the most RAM is the rtx 3090 which is only 24GB, and in my opinion overpriced and inefficient in terms of wattage (~350W). Even the ~$6000 RTX A6000 cards are only 48GB.

Anyone know if that “Device Memory 42.7 GB” is fixed or can be increased?

How will these chips do for training neural nets? The 64 GB RAM would be awesome for larger models, so I’m willing to sacrifice some training speed.

Will the 64GB RAM max chip be practical for training deep learning models? Any benchmarks vs GTX 3090?

Any thoughts on the value proposition if/when >= 64 GB RAM will be available on apple silicon? Even if the chips are relatively slow, the extra RAM could be worth it.

I too am curious how 64 GB unified memory performs for training deep learning models. Even if speed isn't amazing, 64 GB is much greater than the 24 GB available in Nvidia's flagship consumer cards, which would allow for inputting larger images, bigger batch sizes, deeper networks etc. Also, will be interesting to see how all of the different cores are used.

Consider the free PDF of Chollet's "Deep Learning with Python" and/or www.fast.ai

So build more houses?

Are there any good alternatives to Nvidia GPUs/cuDNN for deep learning?

I'm a co-author of this paper and happy to answer any questions.

Genentech (Roche) | Data Science Imaging | South San Francisco | Full-Time | ONSITE

https://www.gene.com/careers/detail/201808-117349/PHC-Data-S...

The PHC Data Science Imaging group seeks a talented and motivated Imaging Data Scientist to join us in supporting the efforts of the Personalized Healthcare (PHC) Group. To aid in the development of novel imaging biomarkers in PHC and their potential use in clinical drug development, the RWD Imaging Group at Roche is responsible for generating and executing plans to: (1) curate and analyze clinical imaging data from Roche’s late stage (Ph3) clinical trials, and (2) devise plans to gain access to (and analyze) clinical imaging data from a RWD setting (e.g., health registries, hospital systems, etc.).

The position requires extensive cross functional collaborations working with a diverse team of clinical subject matter experts, data- and imaging scientists, statisticians, and IT staff. Your responsibilities will primarily support image analysis efforts within the group, focusing especially on applying Machine- and Deep Learning approaches to oncology-, neuroscience-, and ophthalmology projects. In addition to developing and applying novel, data-driven approaches to solving RWD image analysis challenges, the position requires the Imaging Data Scientist to work closely with clinical imaging data management group to deploy, maintain and integrate computational solutions. The job will utilize and build on your experience in scientific/medical imaging, data and image management, application of novel statistical and machine learning approaches to `big data’, software development, and scientific data transfers.

Responsibilities:

Collaborate with internal imaging- and data scientists and external vendors to derive and validate novel imaging biomarkers in support of clinical drug development and RWD evidence (payer support) generation

Identify and gain access to external RWD imaging data sources

Curate/clean/organize large and messy clinical imaging datasets

Identify and support imaging data management solutions within PHC

Continually search for opportunities to automate workflows and streamline processes

Support and contribute to the development of advanced analytics and computational tools

Is there an auditory equivalent?

Maybe we can transform our society into one that is less depressing?

IBM Watson is bad for the "AI" community because when non-experts see IBM repeatedly fail they assume the whole field is nonsense. Hopefully IBM will be more cautious in what they claim to be possible. Hype and deceit do not belong in healthcare.

Very fast. Unfortunately I have only a wifi connection to my house's fiber, but still getting above 100 Mbps up and down. And less expensive and more reliable than comcast.

www.fast.ai

Andrew Ng: Rather than unconditional basic income, there’s a different solution I favor, which is conditional basic income, but conditioned on individuals studying. I think that there’s something in the dignity of work. Rather than paying people to do nothing, I would rather have society pay people to keep studying, because even though many jobs are displaced, there are so many jobs where we just can’t find enough people to do that work.

If we can pay people not to do nothing but instead to study, I think this increases the odds that they’ll gain the skills they need to reenter the workforce. And contribute back to the taxpayers that could contribute to this new engine of value creation for our economy.

At least the possibility of a basic income is being discussed. Humans won't be able to compete with robots that can work 24 hours per day.

I find it hard to believe that "consciousness" can exist in a non-neuronal (or at least non-biological system) , i.e., phi greater than 0 outside of a nervous system. But IIT suggests it can, albeit a small amount, I guess because of back propagation. "If IIT is correct in placing such constraints upon artificial consciousness, deep convolutional networks such as GooGleNet and advanced projects like Blue Brain may be unable to realize high levels of consciousness."

http://www.iep.utm.edu/int-info/#SH4c

I posit the meaning of life is to work toward improving the health of humans and our planet.