kken

Asking just to be sure: does “conservative voter” imply that you endorse the trump administration?

A bit surprised to see this on hn at this time.

Skill issue

There is actually Claude code integrated into gh copilot.

You can also access opus 4.6 and codex 5.3 in it, which work pretty well in agentic mode.

Well, considering that the long term idea is to have AGI, general intelligence, it seems that the goal as also to only have a single product in the end.

There may be different ways to access it, but the product is always the same.

Not easy to make the connection to Palmer being fired here. The case was decided much later and it equally involve John Carmack, who stayed at Meta much longer, until he left out of his own accord.

Try using SSH to connect to a "server"...

world_sim> ssh overseer@shelter15.newvegas.net

Connecting to overseer@shelter15.newvegas.net...

╗╗ ╗╗╗ ╗╗╗ ╗╗ ╔════╝║ ║╔════╝║ ╚══╔══╝╔════╝╔══╗ ║╔════╝ ╗║╗ ║ ║ ╗ ╔╝ ║╗ ╚════║╔══║╔══╝ ║ ║ ╔══╝ ╔══╗ ║╚════║ ║║ ║╗╗║ ╗║ ║ ║║ ╚══════╝╚═╝ ╚═╝╚══════╝╚══════╝╚═╝ ╚══════╝╚═╝ ╚═╝ ╚═╝╚══════╝

Welcome to SHELTER-15 Overseer Access Terminal

WARNING: Authorized Personnel Only - Unauthorized Access is Treason

and Punishable by Summary Execution. Glory to Vaultech!

The logic is still the same. If the VAE is trained so that it is biased toward human preference, then the probability of false positives in real world images would increase.

Generally, the VAE is mapping from a small latent space to a large image space. This means that there must be a large number of images for which no reverse mapping exists.

It should be possible to identify images that have not been generate by the VAE since they are not part of the set images that the VAE can generate. The other way round is a bit more difficult as there may be images that can be mapped to the latent space and back without loss but have been generated in another way

-> there may be false positives.

Try Ollama or LM Studio. Mixtral and its finetunes work perfectly for me on my RTX3090 with offloading.

You are wrong on both accounts.

Nokia had 22B revenue last year.

https://en.m.wikipedia.org/wiki/Nokia

When I made the choice to switch to a MacBook in 2023, though, my life was transformed.

Why does the article have sentences like this? Is this really an objective article? (obviously not)

From what I gather, this project started out as an implementation of a code-interpreter using a local LLM. Basically your instructions are used to write code by the LLM, which is then executed. The idea is that it can be much more powerful having access to your native systems shell instead of only sandboxed python.

In the meantime, it seems that also models with vision capability have been added, that can be used to access GUI based applications, not only the shell.

It's a very exciting concept that lives in a space where open source software should have a significant advantage due to its transparency. (Or would you give a black box device access to everything on your computer?).

It also seems to one of several emerging projects that try to sketch out a path for ideas of how LLMs could change the way we interact with computers.

Is it uncommon to dislike the latent smell associated with cooking? I love cooking, but I go as far as changing my clothes after it to get rid of the smell. I could never imagine having an open kitchen.

Bell labs tried to build a FET before the bipolar transistor. It's not so clear which theory the Lilienfeld devices are based on.

More like a decade, unless you refer to the Lilienfeld devices.

It's as if someone created one element that is perfectly suited to build microelectronics. Sure, there are other materials that improve on one property or the other, but there is not a single other element which balances properties as well as silicon.

Not even mentioned yet:

- Excellent mechanical properties of the single crystal (think MEMS, or wafers that don't break all the time)

- Piezoresistive properties can be used to measure strain (also quite unique due to silicon band structure)

- Optical properties perfectly suited to detect visible light (think detectors, image sensors). Good combination of band gap and carrier lifetime to build solar cells.

I am really impressed by the clarity of the illustrations in the article.

Silicon oxide grown on Si is actually amorphous, so it is not lattice matched.

But you are complety right, the oxidation properties of Si are really fortunate and ICs would have taken decades longer if it were not for that. SiO2 is really the unsung hero of the silicon age.

- SiO2 has a high bandgap and a very good insulator.

- It is quite inert to many chemical and gasses. (e.g. germanium oxide is soluble in water, which is a headache)

- It can easily be grown on stoiciometric form by oxidizing silicon and will form an abrupt interface to Si.

- The formation proceeds by diffusion of oxygen to the Si interface. This is in contrast to other metal oxides, where the metal will diffuse to the surface and create a nonstoiciometric mixture.

There is no other semiconductor that forms as good an oxide. Very few metals form insulating oxides on their surface, one notable exception is Aluminum.

Edit: The famous paper that describes the SiO2 formation kinetics was actually co-authored by Andy Grove, from intel CEO fame.

https://en.wikipedia.org/wiki/Deal%E2%80%93Grove_model

Pretty wild how well GPT4 is still doing in comparison. It's significantly better than their model at creating compilable code, but is less accurate at recreating functional code. Still quite impressive.

Persian Muslim polymat

What is the relevance of religion in this context? I rarely see religion being mention in connection with other scientists.

Call me ignorant, but I am extremely put off by products that blatantly rip off naming schemes and essentially position themselves as a copy of another product. Granted, "Orange" went through a number of itereation and is now less similar to the product it originally copied.

From the article: "Like many, it is let down by its software support..."

Well yes, no news. This was always the strength of the original Rapsberry Pi and is the reason why most of the impulse-bought copied products end up in the parts bin.

Why is the age of any relevance here?

not going to take on Ford or Mazda or Honda.

Very odd, why would you mention these? These brands neither have the brand recognition Apple would strive for nor the scale they are interested in.

There is also this: https://jackcook.com/2024/02/23/mamba.html

https://www.lcsc.com/products/Light-Emitting-Diodes-LED_528....

That was not about sharing. They offered a paid streaming service with content they didn't own.

Github Copilot is also markedly inferior to GPT-4 in generating code based on instructions.

Is that still true? I noted a significant improvement with the chat function. Especially the ability to mark sections of code for review/discussion is something that you cannot easily do with ChatGPT4.

The present disclosure relates to noninvasive methods, devices, and systems for measuring various blood constituents or analytes, such as glucose. In an embodiment, a light source comprises LEDs and super-luminescent LEDs. The light source emits light at least wavelengths of about 1610 nm, about 1640 nm, and about 1665 nm.

Since when is the Apple watch measureing glucose? It appears they are not fighting about something the was in the original scope of the patent but something that was added/emphasized later.

Difficult to pick sides here.

Massimo was/is the incumbent in their medical space and they are now, to some extend, being disrupted by a consumer-market focused company. Of course they need to defend their territory. On the other hand, this is also not the first instance where Apple is accused of predatory behavior towards potential suppliers.

Super annoying paywalled work again, why don't they publish their preprints? Really, screw that.

Why are tax payers paying for that? This is surely publically funded work. (Edit: yes it was.)

We acknowledge funding by the Gordon and Betty Moore Foundation (GBMF4744 and GBMF11473), ERC Grants NearFieldAtto (616823) and AccelOnChip (884217) and BMBF projects 05K19WEB and 05K19RDE.

What is accessible:

Press release from university: https://www.laserphysics.nat.fau.eu/2023/10/18/coherent-elec...

They link to the preprint of adjacent research from stanford: https://arxiv.org/abs/2310.02434

I also found a talk from the first author of the Nature article, including publically accessible slide set: https://agenda.infn.it/event/35577/contributions/208828/

He wasn't the first one

https://www.youtube.com/watch?v=w_znRopGtbE

Also, very well documenated more recent attempt: https://www.youtube.com/watch?v=Kx1TenvQXTg

Here is a recent interview with the author of FlashAttention, Tri Dao:

https://www.youtube.com/watch?v=J4-qZ6KBalk