Sameer Maskey Of Fusemachines

I have brushed against Sameer Maskey at a few events, and he might even know me by name - the New York City Nepali community is small like that, especially since we seem to have a bunch of mutual friends - but there is no mistaking the guy. When you mention "tech startup" to any professional Nepali in the city, they inevitably drop the Sameer Maskey name. I am int the process of going to meet him, hopefully some time next week. I thought I might as well read up on the guy.

Fusemachines: About Us

Sameer Maskey runs a New York-based startup that is building state of the art Artificial Intelligence algorithms for big data Natural Language Processing problems. .... Sameer has a PhD in Computer Science from Columbia University.

Columbia: Sameer
Sameer On Twitter
Next question, please

It’s not every day that someone claims they have the future in their hands, but Dr Sameer Maskey says just that. .... Straight after graduating from school in Nepal, Maskey left for the United States in 1999 where he was to complete his undergraduate, masters, and finally a PhD degree from Columbia University, New York in 2008..... After years of studying and working abroad, the 33-year-old researcher wanted to start a project that could benefit his home country. In 2013, Maskey opened a company called Fuse Machines that would produce, market, and sell conversation systems. ....... The software he is currently developing allows people to text or web-chat a company with a query or complaint and the system will respond with an answer or solution straight away. ....... In laymen’s term, data analysts from Fuse Machines and analysts from their respective clients exchange information based on what kind of services and complaints individual consumers demand of them. This data is catalogued in the system, so when a customer asks a question from within this inventory in any language, the software is able to give the answer. If a consumer asks a question the system does not have the answer to, within 24 hours with the help of an analyst, it will find the solution and retain the answer for next time. ...... Fuse Machines already has an array of e-commerce clients in the US and Maskey says in the coming months a lot of firms based in Nepal will also be using the software. ..... In a country where the most successful companies do not have adequate face-to-face customer service centres, Maskey is hopeful that his conversation systems based on web chats and artificial intelligence will take off and improve the way organisations handle queries and complaints. “Once in a while technology does leapfrog in Nepal, here’s hoping this is one of those times,” says the professor.

Angel List: Fusemachines
Dr. Sameer Maskey

His course is designed to bring MBA students and Computer Science students in the same classroom with the aim of bridging the gap between Computer Science and Business management. Case in point: the booming industry of startups that has taken the western world by storm. ...... Dr. Sameer shares his experiences and views regarding the issue of choosing off beat careers and choosing to become more than a doctor, scientist or business man. Here’s an insight from a man who dared to break the convention and succeeded. ...... What it does is it understands what you said, processes it and converts it into text and speaks back to you. ...... Siri is a voice based application which instigates a lot of errors. Our program is focused on a text to text dialogue which has fewer errors. ...... Imagine calling any company in the world and talking to a machine or robot for customer service which answers all your queries as well as a human. If machines can replace the human function, it increases efficiency and that manpower can be better utilized. ..... I studied at St. Xaviers .... After high school, I enrolled into Army College in Bhaktapur where it wasn’t really common for students to apply for SATs or even apply to study abroad as a whole. In army school you aimed to go into the army. .... I applied to a bunch of colleges where I got a number of full scholarships and chose to study in Bates

BusinessWeek: Fusemachines
CorporateWiki: Sameer Maskey
BusinessWeek: Sameer Maskey

Looks to me like this guy wants to be the world's Call Center.

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Internet Satellites? Now You Have My Attention, Elon

Mars is esoteric to me. I already know what's on Mars. Earth is way more exciting. Glad to have you back on earth, Elon.



$100 Billion Plan To Save The World
Elon Musk’s Next Mission: Internet Satellites

Elon Musk shook up the automotive and aerospace industries with electric cars and cheap rockets. Now, he’s focused on satellites, looking at ways to make smaller, less-expensive models that can deliver Internet access across the globe ..... launching around 700 satellites, each weighing less than 250 pounds ...... it would cost $1 billion or more ..... hopes to bring the cost of manufacturing smaller models under $1 million

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Neuromorphic Chips

Dr. Isaac Asimov, head-and-shoulders portrait, facing slightly right, 1965 (Photo credit: Wikipedia)

Is this what you see on the way to Singularity?

Neuromorphic Chips

Traditional chips are reaching fundamental performance limits. ..... The robot is performing tasks that have typically needed powerful, specially programmed computers that use far more electricity. Powered by only a smartphone chip with specialized software, Pioneer can recognize objects it hasn’t seen before, sort them by their similarity to related objects, and navigate the room to deliver them to the right location—not because of laborious programming but merely by being shown once where they should go. The robot can do all that because it is simulating, albeit in a very limited fashion, the way a brain works. ..... They promise to accelerate decades of fitful progress in artificial intelligence and lead to machines that are able to understand and interact with the world in humanlike ways. Medical sensors and devices could track individuals’ vital signs and response to treatments over time, learning to adjust dosages or even catch problems early. Your smartphone could learn to anticipate what you want next, such as background on someone you’re about to meet or an alert that it’s time to leave for your next meeting. Those self-driving cars Google is experimenting with might not need your help at all, and more adept Roombas wouldn’t get stuck under your couch. “We’re blurring the boundary between silicon and biological systems” ...... Today’s computers all use the so-called von Neumann architecture, which shuttles data back and forth between a central processor and memory chips in linear sequences of calculations. That method is great for crunching numbers and executing precisely written programs, but not for processing images or sound and making sense of it all. It’s telling that in 2012, when Google demonstrated artificial-­intelligence software that learned to recognize cats in videos without being told what a cat was, it needed 16,000 processors to pull it off. ..... “There’s no way you can build it [only] in software,” he says of effective AI. “You have to build this in silicon.” ...... Isaac Asimov’s “Zeroth Law” of robotics: “A robot may not harm humanity, or, by inaction, allow humanity to come to harm.” ..... glasses for the blind that use visual and auditory sensors to recognize objects and provide audio cues; health-care systems that monitor vital signs, provide early warnings of potential problems, and suggest ways to individualize treatments; and computers that draw on wind patterns, tides, and other indicators to predict tsunamis more accurately.

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Don't Push Me, I Am On The Edge

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Neuromorphic Chips Microprocessors configured more like brains than traditional chips could soon make computers far more astute about what’s going on around them.
Genome Editing The ability to create primates with intentional mutations could provide powerful new ways to study complex and genetically baffling brain disorders.
Microscale 3-D Printing Inks made from different types of materials, precisely applied, are greatly expanding the kinds of things that can be printed.
Mobile Collaboration The smartphone era is finally getting the productivity software it needs.
Oculus Rift Thirty years after virtual-reality goggles and immersive virtual worlds made their debut, the technology finally seems poised for widespread use.
Agile Robots Computer scientists have created machines that have the balance and agility to walk and run across rough and uneven terrain, making them far more useful in navigating human environments.
Smart Wind and Solar Power Big data and artificial intelligence are producing ultra-accurate forecasts that will make it feasible to integrate much more renewable energy into the grid.

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Deep Learning

A.I. Artificial Intelligence (album) (Photo credit: Wikipedia)

"..... deep learning, a relatively new field of artificial intelligence research that aims to achieve tasks like recognizing faces in video or words in human speech ..... "

Is Google Cornering the Market on Deep Learning?

Companies like Google expect deep learning to help them create new types of products that can understand and learn from the images, text, and video clogging the Web..... Not everyone is happy about the arrival of the proverbial Google Bus in one of academia’s rarefied precincts..... a cultural “boundary between academia and Silicon Valley” had been crossed ..... deep learning experts were in such demand that they command the same types of seven-figure salaries as some first-year NFL quarterbacks..... Of the three computer scientists considered among the originators of deep-learning—Hinton, LeCun, and Bengio—only Bengio has so far stayed put in the ivory tower. “I just didn’t think earning 10 times more will make me happier,” he says. “As an academic I can choose what to work on and consider very long-term goals.” ..... in December, DeepMind published a paper showing that its software could do that by learning how to play seven Atari2600 games using as inputs only the information visible on a video screen, such as the score. For three of the games, the classics Breakout, Enduro, and Pong, the computer ended up playing better than an expert human. ..... might be particularly useful in helping robots learn to navigate the human world

Have you sometimes wondered, especially if you are someone who takes, uploads and publicly shares a ton of photos, that maybe noone else is seeing all those photos? What if your thing is video not photo? Then definitely even less people are watching the videos. What if there are important nuggets in them? What if it is a problem that no one is watching your videos?

Deep Learning

Deep-learning software attempts to mimic the activity in layers of neurons in the neocortex, the wrinkly 80 percent of the brain where thinking occurs. The software learns, in a very real sense, to recognize patterns in digital representations of sounds, images, and other data. ..... computer scientists can now model many more layers of virtual neurons than ever before ..... remarkable advances in speech and image recognition. ..... Last June, a Google deep-learning system that had been shown 10 million images from YouTube videos proved almost twice as good as any previous image recognition effort at identifying objects such as cats. Google also used the technology to cut the error rate on speech recognition in its latest Android mobile software. ...... a demonstration of speech software that transcribed his spoken words into English text with an error rate of 7 percent, translated them into Chinese-language text, and then simulated his own voice uttering them in Mandarin. ...... image recognition, search, and natural-language understanding ...... machine intelligence is starting to transform everything from communications and computing to medicine, manufacturing, and transportation. .... “deep learning has reignited some of the grand challenges in artificial intelligence.” ..... software that is familiar with the attributes of, say, an edge or a sound ...... This is much the same way a child learns what a dog is by noticing the details of head shape, behavior, and the like in furry, barking animals that other people call dogs. ...... In 2006, Hinton developed a more efficient way to teach individual layers of neurons. The first layer learns primitive features, like an edge in an image or the tiniest unit of speech sound. It does this by finding combinations of digitized pixels or sound waves that occur more often than they should by chance. Once that layer accurately recognizes those features, they’re fed to the next layer, which trains itself to recognize more complex features, like a corner or a combination of speech sounds. The process is repeated in successive layers until the system can reliably recognize phonemes or objects. ...... At least 80 percent of the recent advances in AI can be attributed to the availability of more computer power ...... Until last year, Google’s Android software used a method that misunderstood many words. But in preparation for a new release of Android last July, Dean and his team helped replace part of the speech system with one based on deep learning. Because the multiple layers of neurons allow for more precise training on the many variants of a sound, the system can recognize scraps of sound more reliably, especially in noisy environments such as subway platforms. Since it’s likelier to understand what was actually uttered, the result it returns is likelier to be accurate as well. Almost overnight, the number of errors fell by up to 25 percent—results so good that many reviewers now deem Android’s voice search smarter than Apple’s more famous Siri voice assistant. ..... Some critics say deep learning and AI in general ignore too much of the brain’s biology in favor of brute-force computing. ....... deep learning fails to account for the concept of time .... human learning depends on our ability to recall sequences of patterns: when you watch a video of a cat doing something funny, it’s the motion that matters, not a series of still images like those Google used in its experiment. “Google’s attitude is: lots of data makes up for everything” ...... deep-learning models can use phoneme data from English to more quickly train systems to recognize the spoken sounds in other languages ....... more sophisticated image recognition could make Google’s self-driving cars much better ....... Kurzweil will tap into the Knowledge Graph, Google’s catalogue of some 700 million topics, locations, people, and more, plus billions of relationships among them. It was introduced last year as a way to provide searchers with answers to their queries, not just links. ....... apply deep-learning algorithms to help computers deal with the “soft boundaries and ambiguities in language.” ..... sensors throughout a city might feed deep-learning systems that could, for instance, predict where traffic jams might occur.

It is possible to imagine a city that has zero traffic jams. If all cars are smart, driverless cars, and all traffic is machine coordinated, it is possible to get rid of traffic jams.

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