31–40 of 553 posts
Microsoft and Oculus have hands free controls that actually work. Inside out tracking is progressing quickly. New UX patterns are getting forged.
I'm exited to see what we'll have in a few years time. In my mind its far more exciting than something like crypto but gets much less press.
For a great recent example that get at some of this, see "Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions" - https://arxiv.org/abs/2104.03829
I'm not affiliated with this work but I am building a company in this area (because I'm excited). Company is in my profile.
Data Hubs. It’s queriable like a database but it doesn’t store your data - it proxies all your other databases and data lakes and stuff, and let’s you join between them. Trino is a great example.
I'm not too deep into the data side of things, but this is interesting to think about. Aren't stuff like data lakes and warehouses supposed to address the need for a centralized datastore? Outside of perhaps an easy-to-apply interface, what benefit would a data hub provide over just streaming duplicates from all of your databases into a single data lake like Snowflake?
We used to have to copy and shuffle data into centralized systems so we can query and join it.
Data hubs do away with all that. Stop needing to think about storage. Instead, it’s just about access.
There have always been fringe tools, eg I once did some cool stuff with MySQL spider engine. But modern systems like Trino (formerly called Presto) make it easy. And, I predict, will hit the mainstream soon.
Narrowband IoT data service. Very low power, low bandwidth, cheap, with increasingly great coverage. It’s like an offshoot of LTE but classified as a 5G technology for massive numbers of low power internet connected devices.
nbIoT is justified if I know that the data volume of my "solution" might increase due to feature/scope creep (and replacing the battery/sensor isn't going to become an annoyance in 2-3 years at end of life).
For most use-case LoRaWAN makes more sense but doesn't have the same marketing budget that is available to T-mobile, Vodafone and Co.
Some people say that there's nothing new in it, but to my mind, they're missing the point : the Berkeley Four took what couldn't be appropriated for profit, and built a statement about what computing is... They revealed the Wizard of Oz to everyone, so that anyone with some computing background can build a processor, freely.
And now this freed wizard is working his magic, and will change the computing landscape irrevocably.
I recently came across Polymarket[1] and am really excited about what crypto has in store for prediction markets and insurance. I've dabbled in prediction markets over the years. I think they have a lot of promise but execution is always an issue. Using ETH to create a two-sided marketplace feels much better than having prediction markets decide what one can bet on. More broadly, decentralizing insurance in this way…
Doesn't seem much different than Auger
There are definitely a few players in this space and I'm excited to see where it goes.
It's a novel "Proof of" algorithm (Proof of Space and Time) that front loads the resource needs into a Plotting phase, with a very efficient Farming phase after that to process blocks with transactions. Seems like a much more fair, sustainable model for having a secure digital currency.
It also has an interesting, Lisp based programming language on it.
But what excites me is that it's lead by Bram Cohen, the dude who invented BitTorrent, one of the best pieces of tech I've used nearly my whole tech life.
Advances in computational chemistry and computational materials science. Specially using ML to speed up computation. Computational chemistry is already patchwork of different heuristic approaches. Graph neural networks and even some language models seem very promising addition. If we could simulate and observe what happens with complex chemistry accurately, it would completely change the biology, medicine and materia…
There is the rub. Biological simulations have been written for 40 years now. It's an extremely difficult problem considering how many latent variables are at play, and people have been working on it for a very long time now.