Tag: ai

Fighting for the user

longer term, this will be an AI arm race of sales bots battling user bots.

Comcast cancellation is just the beginning for AirPaper, whose stated mission is to make bureaucracy “surprisingly pleasant.” Next the startup wants to tackle San Francisco parking permit and business tax registration, as well as the visa application process for visiting China.

Sentient animals

In the recently released book, Beyond Words: What Animals Think and Feel, Carl Safina reports on the intricate social interactions, family bonds and distinct personalities observed in mammals such as elephants, orcas, primates, dogs and wolves. Safina delves into the latest scientific research that reveals layers of complex thought and behavior throughout the animal kingdom

Brilliant Green: the Surprising History and Science of Plant Intelligence, makes a case not only for plant sentience, but also plant rights. Interesting, though science fiction authors have been doing thought experiments about this for a long time, e.g. in Ursula LeGuin’s novel “The Word for World is Forest” and in my own “The Uplift War.” Jack Chalker’s “Midnight at the Well of Souls” portrayed sentient plants, as did Lord of the Rings.

A couple more pointers to possible plant sentience:

Roots and fungi combine to form what is called a mycorrhiza: itself a growing-together of the Greek words for fungus (mykós) and root (riza). In this way, individual plants are joined to one another by an underground hyphal network: a dazzlingly complex and collaborative structure that has become known as the Wood Wide Web. This symbiosis is thought to be 450 ma old. The fungi help plants grow by assisting in the delivery of water, phosphorus, and nitrogen. In exchange plants send the fungus food. The network enables plants to communicate with each other. Fungus will even help plants defend themselves.

This one beech tree was cut 500 years ago by a charcoal maker, but the stump is still alive — we found green chlorophyll under the thick bark. The tree has no leaves to create sugars, so the only explanation is that it has been supported by neighboring trees for 500 years.

Solving SAT

GeoS uses a combination of computer vision to interpret diagrams, natural language processing to read and understand text, and a geometric solver, achieving 49% accuracy on official SAT test questions. If these results were extrapolated to the entire Math SAT test, the computer achieved an SAT score of 500 (out of 800), the average test score for 2015.

Energetics of future minds

Unless one thinks the human way of thinking is the most optimal or most easily implementable way, we should expect de novo AI to make use of different, potentially very compressed and fast, processes. (Brain emulation makes sense if one either cannot figure out how else to do AI, or one wants to copy extant brains for their properties.) Hence, the costs of brain computation is merely a proof of existence that there are systems that effective – the same mental tasks could well be done by far less or far more efficient systems.

Thermal Face Recognition

Cross modal face matching between the thermal and visible spectrum is a much desired capability for night-time surveillance and security applications. Due to a very large modality gap, thermal-to-visible face recognition is one of the most challenging face matching problem. In this paper, we present an approach to bridge this modality gap by a significant margin. Our approach captures the highly non-linear relationship between the 2 modalities by using a deep neural network. Our model attempts to learn a non-linear mapping from visible to thermal spectrum while preserving the identity in- formation. We show substantive performance improvement on a difficult thermal-visible face dataset. The presented approach improves the state-of-the-art by more than 10% in terms of Rank-1 identification and bridge the drop in performance due to the modality gap by more than 40%.

Computer-Aided Explanation

the point where AI is helping understanding directly isn’t that far off.

For instance, might it be possible to get the statistical models of language to deduce the existence of verbs and nouns and other parts of speech? That is, perhaps we could actually see verbs as emergent properties of the underlying statistical model. Even better, might such a deduction actually deepen our understanding of existing linguistic categories? For instance, imagine that we discover previously unknown units of language