Artificial Intelligence/Machine Learning Roundup #13

machine learning cartoon

1. An AI speed test shows clever coders can still beat tech giants like Google and Intel

There is a common narrative in the world of AI that bigger is better. This narrative benefits tech giants, helping them attract talent and investment, but a recent AI competition organized by Stanford University shows the conventional wisdom isn’t always true. Fittingly enough for the field of artificial intelligence, it turns out brains can still beat brawn. Read More

2. Amazon Wants to Know Your Waistline

Online retailer Amazon. com is inviting people to an office in New York to measure small changes in body size and shape. The invite comes from Amazon’s new 3-D body scanning unit, an outgrowth of its acquisition last year of computer vision startup Body Labs. Read More

3. The Future is Here Now — Human Augmentation Products Are Ready for Mass Adoption

Part A: Macro observations that human augmentation products have survived the initial hype cycle and are geared for mass adoption

Since the dawn of humanity, humans have endeavored to do more. I believe there is an intrinsic human need to extend the abilities of our bodies. We see this aspiration littered in our superhero comics and movies where the protagonist possesses super human powers, traits desired by most children and many adults. Read More

4. Deep Learning in Crime Detection and Prevention – Amit Kotkar –

As deep learning is currently the most famous technology, it is used in various applications. Their algorithm is based on the observation that certain crime types tend to cluster in time and space. By using historical data and observing where recent crimes took place, they can predict where future crimes will likely happen. Read More

5. How AI will Revolutionize Eye Tracking Technology –

Eye tracking is a way to implicitly measure what makes people give more attention to certain product packs, Advertisements, billboards and many other forms of product marketing. With this blog, we make a case that how AI will lead to better eye tracking analysis technology thereby increasing its adoption to its potential (which we believe is much higher than its current penetration).

Challenges with Eye Tracking Today

Eye-tracking technology — which can determine where in a visual scene people are directing their gaze — can be been widely used in psychological experiments and marketing research, but a lot of complexities involved in the process of eye tracking has kept it from finding consumer applications on a large scale. Read More

6. The Angry Economy Will Kill Us All – Adrien Book –

The economy often appears to be a dark mistress one is either intimate with or is doomed to never understand.
Yet, despite this apparent simplicity, it will come as no surprise that it’s tough out there for many people surviving off this well-known, well-spread, meritocracy-based system of free markets called capitalism. We in the West are slowly realizing that we live in a post-economic world: nominally rich but plagued by things like medical bankruptcies and income inequalities. Read More

7. Talking to AI’s– Where natural language falls short and what UX can do

User interfaces to artificial intelligence (AI) applications are increasingly using natural language. But while today’s chatbots and AI agents can recognize natural language, like English or Spanish, they still cannot engage with humans in natural conversation. 5 FM” or “Find directions to the nearest gas station”), it cannot support a conversational interface, which often require more than two turns. Read More

8. Self-Driving Cars Won’t Need Accurate Digital Maps, MIT Experts Say

One of the truisms of the self-driving car business is that you can’t begin to function properly without super-detailed, constantly updated digital maps that show buildings, trees, and other features.
“Maps for even a small city tend to be gigabytes; to scale to the whole country, you’d need incredibly high-speed connections and massive servers,” says Teddy Ort, a graduate student in robotics at the Massachusetts Institute of Technology’s Computer Science and Artificial Intelligence Laboratory. ”

Reason: The system doesn’t need accurate measurements to the curb, the lane markings, and roadside features like sidewalks, trees, and buildings. Read More

9. Forget AGI, let’s build really useful AI tools

The biggest opportunities in machine learning (ML) today lie not in cracking the next big nut on the path to artificial general intelligence (AGI), but in opening up existing machine learning techniques to more businesses and making them more usable. The tech giants already know this and are investing in democratizing AI to make tools and services more widely available, but the user experience (UX) of machine learning is still overlooked. When we focus on AI as a tool and recognize how crucial usability is to widespread adoption, we can see that there are opportunities to enhance existing AI in ways that have nothing to do with progress toward human-level machine intelligence or artificial general intelligence. Read More

10. How Frightened Should We Be of A.I.?

Precisely how and when will our curiosity kill us. A number of scientists and engineers fear that, once we build an artificial intelligence smarter than we are, a form of A. , a wish-granting genie rubbed up from our dreams, yet each has voiced grave concerns. Read More