Most modern cancer drug treatment is sequenced to at least the specific proteins of the type of cancer it is.

Have breast cancer? Cool. We figure out which of the many variations so that we can give you medications for that exact type of breast cancer.

This sort of specific targeting has been increasing and increasing for the last 20 years. MRNA is the next step of that and is highly likely to be a means or become or for treatments in many other areas.

Sure it does, but that doesn’t make it bad.

Open source code is not the only solution to secure communication.

You can be extremely secure on closed source tools as well.

If they found specific issues with Signal aside from not being allowed to freely inspect their code base, I suspect we would be hearing about it. Instead I don’t see specific security failings just hat it didn’t make the measure for their security software audit.

As an example of something that is closed source and trusted:

The software used to load data and debug the F-35 fighter jet.

Pretty big problem for 16 countries if that isn’t secure… closed source. So much s you can’t even run tests against the device for loading data to the jet live. It’s a problem to sort out, but it’s an example of where highly important communication protocols are not open source and trusted by the governments of many countries.

If their particular standard here was open source, ok, but they didn’t do anything to assure the version they inspected would be the only version used. In fact every release from that basement pair of programmers could inadvertently have a flaw in it, which this committee would not be reviewing in the code base for its members of parliament.

Not being able to inspect their code vs no passing are different things.

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Why is that wall needed? Can you expand on this more?

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Back when I had it, it was a free 2 TB of google cloud storage with the fiber account.

Yes. The free cloud storage doesn’t hurt either

They just rolled out millions in new fiber lines in my area. I had them for internet since 2018, moved out of their area, and now I am in their area getting their service again.

You are incorrect about that stagnation. Google has breathed new life into fiber offerings.

This guy gets it

The model inferred meaning much the same way it infers meaning from text. Short phrases can generate intricate images accurate to author intent using stable diffusion.

The models themselves in those studies leveraged stable diffusion as the mechanism of image generation, but instead of text prompts, they use fMRI data training.

I like how I said, the problem is progress is moving so far you don’t even realize what you don’t know about the subject as a layman… and then this comment appears saying things are not possible.

Lol.

How timely.

I the speed at which things are changing and redefining what is possible in this space is moving faster than any other are of research. It’s insane to the point that if you are not actively reading white papers every day, you miss major advances.

The layman had this idea of what “AI” means, but we have truly no good way to make the word align to its meaning and capabilities with how fast we change what it means underneath.

Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision Decoding: https://aiimpacts.org/2022-expert-survey-on-progress-in-ai/

High-resolution image reconstruction with latent diffusion models from human brain activity: https://www.biorxiv.org/content/10.1101/2022.11.18.517004v3

Semantic reconstruction of continuous language from non-invasive brain recordings: https://www.biorxiv.org/content/10.1101/2022.09.29.509744v1

Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision Decoding: https://aiimpacts.org/2022-expert-survey-on-progress-in-ai/

High-resolution image reconstruction with latent diffusion models from human brain activity: https://www.biorxiv.org/content/10.1101/2022.11.18.517004v3

Semantic reconstruction of continuous language from non-invasive brain recordings: https://www.biorxiv.org/content/10.1101/2022.09.29.509744v1

A large language model took a 3 second snippet of a voice and extrapolated from that the whole spoken English lexicon from that voice in a way that was indistinguishable from the real person to banking voice verification algorithms.

We are so far beyond what you think of when we say the word AI, because we replaced the underlying thing that it is without most people realizing it. The speed of large language models progress at current is mind boggling.

These models when shown FMRI data for a patient, can figure out what image the patient is looking at, and then render it. Patient looks at a picture of a giraffe in a jungle, and the model renders it having never before seen a giraffe… from brain scan data, in real time.

Not good enough? The same FMRI data was examined in real time by a large language model while a patient was watching a short movie and asked to think about what they saw in words. The sentence the person thought, was rendered as English sentences by the model, in real time, looking at fMRI data.

That’s a step from reading dreams and that too will happen inside 20 months.

We, are very much there.