4 ms·

Machine learning seems to be a meme on the rise right now. What kind of startups are possible in that domain?

by itmag 15y ago

marshallp 15y ago
self driving cars autonomous helicopters automated analysis of satellite imagery search engines visual search engine (google goggles) virtual assistant (siri) speech recognition document classification (spam detectors) question answering systems (ibm watson) ad placement (google adsense) computer guided surgery high throughput imaging (chemo/bioinformatics) product recommendation (amazon/netflix) acturial science industrial automation (inspection systems) intelligent video surveillance
- itmag 15y ago
  Nice! I think I should look into this. I sense that I lack a general understanding of what is really possible with ML. (My current understanding is weighted toward underestimating what is possible with ML).
  - wfaler 15y ago
    That's a very good list. I think we're just starting to scratch at the surface of what is possible, which is why I've devoted myself to working in this field!
- ralphc 15y ago
  I got most of these right away, but could you expand on what you mean by "high throughput imaging (chemo/bioinformatics)"?
  - marshallp 15y ago
    robots chugging away at petri dishes that contain hundreds of mini-dishes with chemicals/biostuff. Making sense of the millions/billions of data points is the job of machine learning.
  - polyfractal 15y ago
    The high throughput imaging that I'm familiar with is in regards to cell imaging. Cells are cultured in high-density plates (96-well or 384-well dishes), each well is given a different experimental condition (drugs, RNAi, etc) and then imaged on an automated microscope. As you can imagine, this generates tons of data. Our lab did a highthrouput screen of genetic mutants in neurons, and then used software to quantify basic morphology such as neurite length , arborization, and cell death. Crystallographers will use a similar system to bathe their protein in billions of compounds to find the right combination for crystallizing. Automated cameras will capture images and try to identify which ones have crystallized so the researcher doesn't have to do it by hand.
vedant 15y ago
Machine learning is concerned with developing algorithms that enable programs to use data to evolve new behavior. Calling it a meme seems to put it in the same category as advice animals and Old Spice ads. Still, I see what you're saying--- it is really "in" right now, which is probably because: (1) There's a lot more data now for people to use it with (2) Infrastructure for doing it is cheap and scalable (3) Automation is a key driver of progress, and ML algos are now getting good enough to automate a lot of stuff that humans used to have to do.
- itmag 15y ago
  Yeah, that's exactly what I meant. I think the online ML class (Stanford?) is helping to pump up interest in the laycrowd.

Machine learning seems to be a meme on the rise right now. What kind of startups are possible in that domain?

by itmag 15y ago

Machine learning seems to be a meme on the rise right now. What kind of startups are possible in that domain?

self driving cars autonomous helicopters automated analysis of satellite imagery search engines visual search engine (google goggles) virtual assistant (siri) speech recognition document classification (spam detectors) question answering systems (ibm watson) ad placement (google adsense) computer guided surgery high throughput imaging (chemo/bioinformatics) product recommendation (amazon/netflix) acturial science industrial automation (inspection systems) intelligent video surveillance

itmag 15y ago
Nice! I think I should look into this. I sense that I lack a general understanding of what is really possible with ML. (My current understanding is weighted toward underestimating what is possible with ML).
- wfaler 15y ago
  That's a very good list. I think we're just starting to scratch at the surface of what is possible, which is why I've devoted myself to working in this field!
ralphc 15y ago
I got most of these right away, but could you expand on what you mean by "high throughput imaging (chemo/bioinformatics)"?
- marshallp 15y ago
  robots chugging away at petri dishes that contain hundreds of mini-dishes with chemicals/biostuff. Making sense of the millions/billions of data points is the job of machine learning.
- polyfractal 15y ago
  The high throughput imaging that I'm familiar with is in regards to cell imaging. Cells are cultured in high-density plates (96-well or 384-well dishes), each well is given a different experimental condition (drugs, RNAi, etc) and then imaged on an automated microscope. As you can imagine, this generates tons of data. Our lab did a highthrouput screen of genetic mutants in neurons, and then used software to quantify basic morphology such as neurite length , arborization, and cell death. Crystallographers will use a similar system to bathe their protein in billions of compounds to find the right combination for crystallizing. Automated cameras will capture images and try to identify which ones have crystallized so the researcher doesn't have to do it by hand.

vedant 15y ago

Machine learning is concerned with developing algorithms that enable programs to use data to evolve new behavior. Calling it a meme seems to put it in the same category as advice animals and Old Spice ads. Still, I see what you're saying--- it is really "in" right now, which is probably because: (1) There's a lot more data now for people to use it with (2) Infrastructure for doing it is cheap and scalable (3) Automation is a key driver of progress, and ML algos are now getting good enough to automate a lot of stuff that humans used to have to do.

itmag 15y ago
Yeah, that's exactly what I meant. I think the online ML class (Stanford?) is helping to pump up interest in the laycrowd.