gjmulhol

Not only is this from 2018, but Yaghi himself demonstrated MOFs in 1995 so "new" is pretty relative.

I have very mixed feelings about this. It is an incredible amount of trust in Apple (both security and actual execution, esp given their history in AI), but it would be such a massive upgrade to individual user security that it is hard to comprehend.

This is really cool...these LLM-like models in technical disciplines are going to open up he new frontiers in science.

Come join our team -- super exciting technical problems of both the engineering/development and chemical engineering/materials science varieties!

This is a good list with some good advice.

As a personal anecdote, I had a very well-known investor tell me that my business would never make more than $5m per year (not venture scale). And this was even knowing that my business is a pretty standard enterprise software business model. We are well past that at this point, so I am proud to have proved him wrong.

This is cool in concept, but the live demo doesn't seem to be working. Or maybe I am using it wrong?

Want to use your CS/dev skills to help solve this problem? Come join us at Citrine Informatics: https://citrine.io/careers

Cool, and definitely useful for complicated data structures

One of the big questions is whether we can extract these minerals from existing devices that are out of use/have been disposed of. Ideally, that means that we are designing new devices with disassembly in mind. Everyone from Apple to Huawei is talking about doing this, but the proof will be in the pudding.

Some of the comments are slightly inaccurate. We actually don't know where all the deposits are, and there was just a large discovery of rare earth elements off the coast of Japan. Much rare earth extraction has been happening in China because of relatively lax environmental standards that have reached back decades, so the US, Australia, and many other countries with deposits can't compete due to the costs of labor and complying with environmental standards and regulations. Mountain pass is one of a few deposits in the US, and happens to be one of the larger ones that is sitting idle. There are lots of mines globally and could be more, but economically they need to be attractive.

Copper is another interesting element. It is exceedingly hard to extract from existing devices because it is buried inside the chips, boards, etc. You can recover about 25% of the copper in a device, or about 3% of the total mineral content of a device when you extract copper. Widespread copper mining has destroyed parts of the Atacama desert in Chile and is a really nasty process.

Finally, work has been going on for a long time to replace rare earth elements or dramatically reduce how much is used. In some cases, you need small amounts because you need those f-orbital electrons but you can get away with using creative coatings instead of large volumes of materials. In other cases, you can replace them by multi-layering other materials to approximate their performance. There are huge opportunities here, but we are a couple decades away from seeing any real sea change in what our devices are made of.

Building physics and chemistry domain specific machine learning systems at Citrine Informatics. It's the best of both the physical science world and the data science world, has really hard problems, works with big companies and has big contracts, and is a team where more than half the people have technical graduate degrees.

This article is spot on. Using AI and ML in an enterprise setting is about changing behavior and helping people to understand why the AI/ML system is making the recommendations (or whatever the output is) that it is. I have seen this in dozens of companies now: even great AI requires cultural change to succeed. And good cultural change can make only mediocre AI models into game changers.

I have had good luck using SE Asia (in our case Singpore) for serving the region. The undersea cable map (https://i.redd.it/eo6248sth0pz.png) shows that it is probably your best bet, but as magicbuzz says, it is likely too far for anything where latency makes to pay a major price, which is most things these days.

Most people in the industry talk about Additive Manufacturing instead of 3d Printing for industrial metals AM.

Well...we found the line...

Focusing on quarterly goals or the like just glosses over this as an issue. It is important that men be willing to say "that isn't how we talk around here" or "man, that is a pretty crude thing to say to someone in a professional environment." If you have the power, comments like that should be met with "you're fired" because honestly, if someone in my workplace can't maintain some sense of decorum around women, how should I expect him (in this case, always a him) to behave around clients, investors, etc.

This is not something around which to dance lightly. It is far too common, and it only takes a few people willing to stand up and say that this isn't acceptable to break the norms of a bunch of guys just laughing along while a few say crude things.

Is this actually a setback? While AI will undoubtedly have an impact in medicine, Watson is an NLP system-cum-amalgamated marketing machine that from what I have seen has done little more than to undermine the promise of properly implemented AI technologies with a lot of marketing gibberish and half-delivered results.

I think the name Instacart is already taken.

"These are the new leads. These are the Glengarry leads. And to you they're gold, and you don't get them. Why? Because to give them to you would be throwing them away. They're for closers."

http://3.bp.blogspot.com/-TQ8GvYqwOfg/TweSejc8ZgI/AAAAAAAAAC...

Yes, this happens to everyone, but this happens to women much much more. Even well intentioned managers at good companies can find themselves victims to cognitive bias, unintentionally. This article raises specific things to watch out for.

Note: I am a male, a manager, and occasionally guilty of such things.

I agree -- there was also a very "product v. engineering" vibe to it also. Maybe my company is different from most they see, but we don't have product doing code reviews for developers. The place tension can arise seems to be more around the fact that product always wants to move faster and engineering expresses that they can't always do that. I don't think either side is right all the time, but the way the article starts with "Winning battle = product giving into engineering", "losing battle = product being pushed into a better decision by engineering" screams to me of a lack of understanding that in a good organization each party has the best possible information for making decisions that represent the interests of the company from different perspectives, and these meetings are to figure out how those interests align or conflict and sort them out.

This is almost certainly not more random than this: http://www.fourmilab.ch/hotbits/

It is a cool idea.

A truly sad day. I had a chance to meet Bill 4 or 5 times as a student and as an entrepreneur, and you would have no idea that he was such an institution: completely approachable and willing to give advice and support even to a random kid from North Carolina.

How do you know they have traction if they won't share numbers.

It is fine to not share everything. Numbers are scary and can be used out of context to make people very fearful. A 10% drop in revenue from month to month could look really scary but actually just be natural business variation. I would say you should trust the team, and that trust should lead to their sharing their vision and numbers to support that vision, but you should not have to have constant access to company financials necessarily.

Pejman is a good dude with an amazing history.

MongoDB is web-scale.

Maybe, but a lot of companies, even in YC, focus on a lot of things that are not related to revenue (unpaid user growth etc).

Wow, I was under the impression that the Flint situation was primarily driven by bad policy put in place by people who didn't really know what they were doing, but it seems like there was a lot more nefarious action than that.

My friends, we are finally hitting the new economy where even startup are being asked to make money---maybe not to the point of profitability, but even a little revenue can make a big difference in a lean organization.

I really like this idea. We groom our Kanban board, which creates a similar effect, but not so explicitly.

In your case or ours, one of the nice things about stepping back is reprioritization, which happens nicely in Scrum but not so much in Kanban. It is easy to define a path and never diverge only to wake up and realize you built an old vision.

I love this. We briefly flirted with scrum but now just have a much more Kanban-like system now, too. The only issue I foresee long term is that the sprint mentality of Scrum might recharge people and get them to, well, sprint, at product goals. Kanban, because it is never ending, might start to feel like a slog. There is never a way to have that feeling of "wow, we crushed it and cleared out our list. We are awesome." The list just extends forever. We have put measures in to help with this: primarily just having our engineers say at the beginning of the week what they hope/plan to get done this week (or two). Sometimes that is just noting subtasks in pursuit of a larger feature, but at least it borrows some of what is a very powerful part of Scrum: the social commitment that comes from standing up and saying "this is what I will finish this sprint."