191–200 of 407 posts
An important trend is the API-ification of everything. As more and more businesses are accessible with a web API, the Internet becomes more and more powerful. I'd like to invite people to try the early release of Empire API, which is one API for every enterprise SaaS: http://empiredata.co Empire is an API for accessing enterprise SaaS services such as Salesforce, Zendesk, Google Apps, etc. It provides a uniform, data…
While I've always felt a strong attraction to YCombinator (especially the cameraderie that comes from being a part of it) and been very inspired to apply, I can't help but feel that I am in a phase of life that's simply not a good fit for YC, or at least the narrative that's pushed. I'm no longer a mid 20-something that can live on Ramen and 16 hour days. I'm married and have a young child. Are there YC founders in t…
"This is one reason I'd bet on the 25 year old over the 32 year old."
"By 38 you can't take so many risks-- especially if you have kids"
I would be wary approaching an organization that has publicly expressed such age discrimination.
Would somebody please disrupt the textbook publishing industry? http://www.amazon.com/Discrete-Mathematics-Applications-Susa... $264.39, for students that work part time jobs at $7.00 an hour (before taxes). Not only students are angry about this. Professors are angry, and authors are angry too. Bitter fights between professors and publishers are common. Everybody wants to see the big players in this industry fail .…
I have been working (and still am working) with incredibly expensive software from IBM. Now it's somewhat trivial what it does and I have open sourced it (http://www.use-the-tree.com). Feel free to contact me. My dream is to find a team, apply to YC and crush IBM (I am somewhat serious).
Would somebody please disrupt the textbook publishing industry? http://www.amazon.com/Discrete-Mathematics-Applications-Susa... $264.39, for students that work part time jobs at $7.00 an hour (before taxes). Not only students are angry about this. Professors are angry, and authors are angry too. Bitter fights between professors and publishers are common. Everybody wants to see the big players in this industry fail .…
Cost of attendance at my state flagship is $24,000. Full time at minimum wage is $15,080. Any education worth that kind of money is hard enough that you physically can't work full time while doing it. Student labor is pretty miniscule as a source of funding.
In other words, $264.39 is not actually 37 hours at McDonalds. It's a rounding error on a parent's 6-figure contribution over 4 years. Or a rounding error in your monthly loan payment when you're making $50k instead of $8k. Or it's coming out of interest on the school's endowment if the school is good enough and your family poor enough. Or it's coming from whoever funds your scholarship if you are one of the handful of people smart enough to get a merit-based full ride. Etc.
(No, your experience of putting yourself through a state flagship in the 80s is not relevant. Minimum wage is roughly what it was; tuition is decidedly not.)
I believe the textbook publishing industry could adapt (or be disrupted) to be more cost-efficient, but you would first have to vastly reconfigure the higher education system such that it's reasonable for students to pay their own way. Then you'd actually have incentives to price things for students.
> What comes after programming languages? I've been working on this for several years, though a startup seems the wrong vehicle for it. I think the description in the RFS is misguided: "We’re interested in helping developers create better software, faster. This includes new ways to write, understand, and collaborate on code, and the next generation of tools and infrastructure for delivering software continuously and…
This is a great point. I am always struck by how there are so many times where, if I could sit down with the original program author for 5 - 10 minutes, I could understand more from that interactive back-and-forth than several hours of reading code in solitude. This tells me it's not that understanding how that code works is intellectually difficult; rather it's discovering how it works is time-consuming. It would be…
So you could choose to hear what the author was saying right when he was working on a certain area of the code. (You'd normally turn it off, but if you're really stuck it might be a good last resort.)
> What comes after programming languages? I've been working on this for several years, though a startup seems the wrong vehicle for it. I think the description in the RFS is misguided: "We’re interested in helping developers create better software, faster. This includes new ways to write, understand, and collaborate on code, and the next generation of tools and infrastructure for delivering software continuously and…
I'm pretty sure that our assumption that programming languages will look like programming languages in the future is sort of like the assumption that phones will always have buttons on them. Once Apple and other companies showed what the world looks like when a phone is a giant touch screen + giant battery, phones with buttons become a niche, not the norm. I don't know what the programming paradigm is that completely…
> We’d like to see new services that make it possible to invest in super low-cost index funds. Sorry, this is not the right problem in financial services. Companies like Vanguard are already doing a great job of this and the costs are extremely low. Its a commodity product with razor thin margins that actually serves the needs of its customers well. Maybe there's a marketing issue where they aren't educating enough p…
IPOs are sales problems, which require high touch interaction and networking. They are also dangerous to get wrong which is why companies pay high fees to do them. Remember too that Google got burnt by trying to avoid the sales process entirely.
> What comes after programming languages? I've been working on this for several years, though a startup seems the wrong vehicle for it. I think the description in the RFS is misguided: "We’re interested in helping developers create better software, faster. This includes new ways to write, understand, and collaborate on code, and the next generation of tools and infrastructure for delivering software continuously and…
I'm pretty sure that our assumption that programming languages will look like programming languages in the future is sort of like the assumption that phones will always have buttons on them. Once Apple and other companies showed what the world looks like when a phone is a giant touch screen + giant battery, phones with buttons become a niche, not the norm. I don't know what the programming paradigm is that completely…
I think "naked objects" or "apache isis" are the best examples we've got for that for now , but they are rooted in somewhat complex java code, instead of being rooted in an easy to use tool, such that lets the business analyst who had some course , sit with the client and fully define a running system , step by step. In some cases the auto-generated UI would be good as it is , and the system will be used as-is.
In other cases , we might need easy tools to customize the UI.
Earlier quoted context omitted.
These have traditionally been domains requiring a huge research apparatus with tremendous manpower, for only very long term gains. Not good for startups. In AI, how can a startup hope to succeed when academia has had almost no success in 50 years (and I am doubtful throwing more CPU/neuron layers will 'solve' the problem). This is a pure example of the AI Effect[1]. Academia has been extremely successful with AI Rese…
Interesting link, but I still feel AI hasn't had much success: Do we really have much more today that A* search, neural nets with backpropagation, and HMMs/SVM/etc, which were all developed in the 1960s? The successes of AI that I see (eg OCR/speech recognition and Chess/Jeopardy) use these same old algorithms with only marginal improvements and more CPU. There have been no new major techniques or insights. I'm not a…
That said, some more recent work comes to mind.
In terms of new algos: planning algorithms, deep learning architectures (ANNs without backprop), reinforcement learning, alife and multi-agent systems.
In terms of applications (which you already hint at): Deep Blue and Watson, both of which are great examples that shouldn't be regarded so trivially. Is the only difference between the "old algorithms" from the 1960s and Watson challenging people on Jeopardy is a matter of margin? No. It's not as if we were nearly there in the 60s and only needed to crank up CPU or RAM speed/storage. Read IBM's paper on it -- it took a complex architecture spanning natural language processing, databases, search, and machine learning. As for Deep Blue, even in the early 90s people said there would never be an AI to beat the best human Chess players. Once it happened, the paradigm shifted and "of course" AI can beat humans at Chess, as if there hadn't been who denied it was possible.
Some of the coolest more recent applications are in the realm of machine learning: self-driving cars, robots that learn to navigate or perform tasks, and image recognition (which has made an immense leap in the past ~2 years).