Today we look at the ways in which AI is making science fiction a reality.Futurismfeatured a number of products, such as an earpiece which serves as an instant translator and a Star Trek-esque Medical Tricorder.
We wanted to ask you: what is your favourite example of science fiction becoming a reality? Head over to the surveyto voice your opinion.
A commonly held view of hedge funds is of secretive organisations that jealously guard the tools that make them money. Contrary to this is the trend among certain firms to open source their software and invite collaboration from the developer community. Firms that have blazed a trail in the open sourcing of this sort of technology are the likes of AQR, which kick-started the Pandas libraries project, and Man AHL, which has open-sourced its Arctic data storage system.
Gary Collier, Co-CTO of Man AHL is taking part in a session on open source technology at Newsweek/IBT’s forthcoming Data Science in Capital Markets event which we at CognitionX are proud to be a partner of, alongside Wes Mckinney, who created Pandas. “Open sourcing things is really one way of raising a virtual flag above the office which is saying, the ideals that you as a brilliant developer hold dear – community engagement, openness, collaboration – are also ideals that our business holds dear,” said Collier.
Futurism features some exciting prototypes, such as the Medical Tricorder, which are bringing science fiction to life. The tricorder is one of Star Trek‘s most famous unrequited innovations. Catalyzed by a new XPRIZE competition from Qualcomm, companies across the US are working hard to bring it to life. One of the finalists, Cloud DX, possesses a prototype that is particularly transformative.
This course begins with a study of finite automata and the languages they can define (the so-called “regular languages.” Topics include deterministic and nondeterministic automata, regular expressions, and the equivalence of these language-defining mechanisms. It also looks at closure properties of the regular languages, e.g., the fact that the union of two regular languages is also a regular language. Next, decision properties of regular languages are considered, e.g., the fact that there is an algorithm to tell whether or not the language defined by two finite automata are the same language. The course continues with the pumping lemma for regular languages — a way of proving that certain languages are not regular languages. Also included in this course are context-free grammars, the Turing machine, and the theory of intractable problems.
In this study, Peter Florian Neher, Marc-Alexandre Cote, Jean-Christophe Houde, Maxime Descoteaux, Klaus H. Maier-Heinpresent a fibre tractography approach based on a random forest classification and voting process, guiding each step of the streamline progression by directly processing raw diffusion-weighted signal intensities. For comparison to the state-of-the-art, i.e. tractography pipelines that rely on mathematical modeling, they performed a quantitative and qualitative evaluation with multiple phantom and in vivo experiments, including a comparison to the 96 submissions of the ISMRM tractography challenge 2015. The results demonstrate the vast potential of machine learning for fibre tractography.
Romania biometric firm TypingDNA is developing AI-based behavioural biometrics that the firm says are a viable replacement for other, more established modalities. Speaking to PCWorld, staff said the accuracy for matching typing-based “fingerprints” to individual persons by using traditional statistical analysis and mathematical equations varies around 60 percent to 70 percent.
However, Raul Popa, CEO and data scientist, said this has been transformed in the past two or three years due to advances in machine learning. The company said it has used these advances to develop AI-powered typing pattern recognition technology that it claims has an accuracy of more than 99 percent and can even reach 99.9 percent when there is a sufficiently large typing profile built for the user over time.
UEBA is correlation on steroids, capable of detecting anomalies that can indicate if staff logins have been compromised and are being tested across the enterprise network. It can learn the activities and services most typical of a user to generate alerts when something anomalous occurs.
In principle, reinforcement learning and policy search methods can enable robots to learn highly complex and general skills that may allow them to function amid the complexity and diversity of the real world. However, training a policy that generalizes well across a wide range of real-world conditions requires far greater quantity and diversity of experience than is practical to collect with a single robot. Fortunately, it is possible for multiple robots to share their experience with one another, and thereby, learn a policy collectively.
Ankesh Kumar, Founder and CEO of Personic.AI, is one of the pioneers of chatbot messaging whose company has built chatbots for brands around the world. He said to Murray Newlands from Forbes, “Personic.ai are working with a number of companies in the food and drink area, making suggestions on food that would fit your taste palate and drinks that would go with your meals. We all have to eat, why not maximize your enjoyment? The bots we’re seeing are building taste profiles and personalizations. Over time, the bot will learn more about you and what you like and can make more suggestions. Some people may think it’s a little creepy, but we already see that when ads pop up when you go to website. We’re there already.”