axg11

Yes: Deep Research (OpenAI/Google/Perplexity), Devin, Ribbon.ai to name a few.

There are plenty.

I wrote an in-house one for Ribbon. If there’s interest, will open source this. It’s amazing how much better our LLM outputs are with the reducer.

Two-way interaction is of course valuable but it's only valuable with the team you'll actually be working with. You will never work with the recruiter who is responsible for your screening interview.

I've heard this sentiment. Have you been through a screening interview with a recruiter before? It's most often very formulaic and they don't have expertise in your domain. On top of that you have to find a mutual time that works for the recruiter 9-5pm.

With this approach you can interview anytime 24/7 and get a consistent experience.

Fixing the Firefox issue - thanks for pointing that out.

Great point. Here's a video below but I'll work on un-authed access.

https://imgur.com/wIaGDrU

I would change the main CTA to "Try it now" and then use a different style for "Read the stats". It currently looks like there are two equally important CTAs.

If you can find a way to make the results closer to real-time, this will be a really popular product.

This is a sensible strategy. Apple finally revealed their cards after 5+ years of rumours surrounding the Apple Vision Pro. Meta doesn't have the brand strength to launch a true high-end XR headset that can compete with the Vision Pro. Instead, they're trying to capture the lower end of the market.

Go one level deeper and you'll find the problem with all of academia (source: I have a PhD).

Most of academic science as we know it today is structured so that the output is "publishable" and/or helps future grant applications. Incremental improvements are very publishable, but that doesn't necessarily make good science. Grants are awarded to scientists who are consistently able to deliver results, in the form of published papers. I can only really speak for my little corner of science, but from my view, the entire incentive structure of science is broken.

Ribbon | Remote or On-Site | Toronto, Canada | Full Time https://ribbon.cool

Ribbon is to LinkedIn as BlueSky is to Twitter. We're rebuilding the world of professional social networks and employee recognition to be centred on one thing: ownership. We believe that everything you accomplish and achieve should be recognized and owned by you (not by a third party). When you move between organizations, your achievements and benefits should move with you. Ribbon is "Proof of Achievement".

We’re backed by top tier investors and operators from across the globe. We’re hiring full stack developers for our founding team - join us!

More info here: https://ribbon.cool and here: https://ribbon.cool/hiring

To apply email arsham[at]ribbon[dot]cool

Ribbon | Remote or On-Site | Toronto, Canada | Full Time https://ribbon.cool

Ribbon is to LinkedIn as BlueSky is to Twitter. We're rebuilding the world of professional social networks and employee recognition to be centred on one thing: ownership. We believe that everything you accomplish and achieve should be recognized and owned by you (not by a third party). When you move between organizations, your achievements and benefits should move with you. Ribbon is "Proof of Achievement".

We’re backed by top tier investors and operators from across the globe. We’re hiring full stack developers for our founding team - join us!

More info here: https://ribbon.cool and here: https://ribbon.cool/hiring

To apply email arsham[at]ribbon[dot]cool

Ribbon | Remote or On-Site | Toronto, Canada | Full Time

https://ribbon.cool

Ribbon is rebuilding the world of professional social networks and employee recognition to be centred on one thing: ownership. We believe that everything you accomplish and achieve should be recognized and owned by you (not by a third party). When you move between organizations, your achievements and benefits should move with you. Ribbon is to "Proof of Achievement" as Worldcoin is to "Proof of Human".

We’re backed by top tier investors and operators from across the globe. We’re hiring full stack developers for our founding team - join us!

More info here: https://ribbon.cool and here: https://ribbon-awards.notion.site/Ribbon-d8e4aecc4c064e89a8d...

To apply email arsham[at]ribbon[dot]cool

I don't think _this_ is a security check. These are essentially unlisted plugins. They will be released/approved and this is a way to allow some user to test the plugins (different client side software).

What would it even mean to be an open source Cloudflare? The entire point of Cloudflare is that they run the tricky stuff for you. As another user said here, you can use nginx and lots of other OSS to achieve the same end goals. You will work much harder for it though.

A key detail a lot of people are missing about "traditional" search vs. ChatGPT style search:

ChatGPT/LLMs can essentially crawl _anything_ they want, regardless of legality, license, consent, etc. These models are trained on anything that can be ingested. Once trained, you can release the model with plausible deniability. There's no 1:1 relation between ingested content and outputs. LLMs that "cheat" by ingesting content they shouldn't have will have an advantage over those that don't.

Google and other search engines don't have this luxury. If they serve a result, they have to make sure that they're not violating any license. If they crawl the wrong content, they have to make sure they don't serve it.

I disagree that LLMs are overhyped, but it's very subjective. Are current LLMs a few steps from AGI? No. Will LLMs change the computing landscape? Yes, I believe they will.

ChatGPT, without any major changes, is already the best tool out there for answering programming questions. Nothing else comes close. I can ask it to provide code for combining two APIs and it will give useful and clean output. No need to trudge through documentation, SEO-hacked articles, or 10 different Stack Overflow answers. Output quality will only improve from here. Does it sometimes make mistakes? Yes. There are also mistakes in many of the top SO answers, especially as your questions become more obscure.

Aside from programming, how many other fields are there where LLMs will become an indispensable tool? I have a PhD and ChatGPT can write a more coherent paragraph on my thesis topic than most people in my field. It does this in seconds. If you give a human enough time, they will be able to do better than ChatGPT. The problem is, we're already producing more science within niche scientific fields than most scientists could ever read. As an information summary tool, I think LLMs will be revolutionary. LLMs can help individuals leverage knowledge in a way that's impossible today and has been impossible for the last 30 years since the explosion in the number of scientific publications.

ChatGPT is actually quite good at this and I think it's a hint at the future of alignment. Many (most?) of the responses from ChatGPT are along the lines of: I don't know, I can't know, I can't respond, etc. It's still far from perfect but I think exploring the results of human feedback for alignment is one of the reasons OpenAI decided to release ChatGPT rather than rush straight to GPT4 (larger model, more data, retrieval, etc.).

Ribbon | Remote or On-Site | Toronto, Canada | Full Time

http://ribbon.cool/careers

Ribbon is rebuilding the world of professional social networks and employee recognition to be centred on one thing: ownership. We believe that everything you accomplish and achieve should be recognized and owned by you (not by a third party). When you move between organizations, your achievements and benefits should move with you.

We’re backed by top tier investors and operators from across the globe (to be announced soon - we're currently semi-stealth).

We’re hiring full stack developers for our founding team - join us!

More info here: http://ribbon.cool/careers To apply email arsham[at]ribbon[dot]cool

I like the aesthetic -- a modern warm Craigslist?

Internally that's the long term goal. Essentials/basics lines exist because Amazon has superior data on what their customers search for and return rates etc. Parts of leadership wants to open up more of that data to third party sellers and let the free market sort itself out.

Amazon Ads is going to be a really interesting corporate case study in ~10 years. A combination of factors are coming together that will eventually result in the death of Amazon's retail division.

Amazon has been doubling down on ads in retail search results over the last ~4 years. Ad load (e.g. "Sponsored Products") has been steadily increasing. One of the main reasons is that Ads as a group has incredible margins (the marginal cost of displaying an advert is ~$0). As a result, Ads has been crushing all KPIs, leading to more resources dedicated to the Ads org. The growing teams and increased headcount in the org have had to justify their existence through revenue growth. What's the easiest way to grow an advertising org? Show more ads!

The above is simplifying things, but the bottom line is that Amazon.com today shows a lot more ads than four years ago. Concurrently, Amazon has aggressively shifted away from directly selling goods itself towards third party sellers. Amazon.com is now predominately a marketplace of third party sellers all competing against each other to appear at the top of the search results. The only way to consistently appear at the top of retail search results is to be the highest bidder for marketplace ads.

All of this has really distorted incentives for third party sellers. They no longer need to have the best product to get sales. They're incentivized to spend more on ads and less on the product itself. Product quality is noticeably worse than in the past and it's still getting worse. To battle that, sellers leave fake reviews. Customers lose trust in Amazon and become more wary of what they buy.

These factors are self-reinforcing -- hence why I think Amazon will be an interesting case study. Once you lose customer trust, it's hard to get it back. They can try to combat this with a great return policy and customer service, but the incentives are still misaligned.

Context: used to work for Amazon Ads org

Internally it was sold as: working together with other teams is too inefficient due to dependencies and differing priorities. It's faster to build it again independently than integrate with the existing service.

Success is relative. Voice didn't turn out to be "the next big computing platform". It's still mostly a command interface. Perhaps it still could become something bigger. Alexa isn't widely used on the iPhone/iOS/CarPlay or Android/Android Auto, the two most important places for voice. Alexa works well but doesn't have a clear technology advantage vs Google Assistant (admittedly, Siri is trash).

Contrast that to VR, which is in a much earlier stage of its technology and adoption cycle: Meta has a strong technology advantage, currently has the best overall platform and _if_ VR becomes the next big computing platform, Meta is in a strong position to capture a significant proportion of market share. It's a big if! but at least there's still a chance.

Context: I recently left Amazon

Some orgs within the company are fairly lean, some are hugely bloated. Amazon isn't homogeneous. For example, Alexa is very over-resourced and it's common to hear about 4+ teams working on slight variations of the same project. Lots of redundancy there. I believe Alexa as an org is losing $5b+ per year. Contrast that to all the criticism Facebook is receiving for their investment into VR/AR. The investment in Alexa was a platform play. Amazon thought that voice would be the next big platform. I'm not sure results and trajectory justify the investment anymore.

This is really impressive. The speed record itself is not super relevant to everyday production vehicles, but it's a great way to win customers over to EVs.

In general, I underestimated the progress that electric vehicles would make over the last ~2 years. Most manufacturers have at least one decent EV on the market now. Where I live (Toronto, Canada), EV charging infrastructure still needs a lot of improvement but it's an inevitability now.

There's no profitability from navigation? Starlink could charge a massive premium for high resolution GPS.

How many founders are claiming rent as a business expense? Granted, founders are able to expense a lot of things that employees are not.

I largely agree with the take that Uber is an inefficient company, but I don't think Uber is as simple as "an app company". Uber's main challenge is people. They're basically one of the largest employers on Earth (est. ~4 million drivers). They operate across all regions. All of that adds complexity.

Is there anything like this for a wider basket of (tech) companies?

Typically 10-20% but the correct answer to this question is "it varies".

Anytime you perform a sequencing experiment you will get _some_ microbial/fungal contamination. Every time. You can even check this yourself today. Analyse any publicly available (unprocessed) whole genome sequencing data. Usually the contamination is <1% but it’s there.

This study hasn’t ruled out contamination as the cause for the results. Given that, it’s very likely to be BS.