Image 05 March 2019
Image
 
Image

Renewable Energy

AI Trained to Predict the Energy Output of Google Wind Farms

DeepMind, a London-headquartered AI lab that was acquired by Google in 2014 claims that it has trained an AI system to predict the energy output of Google wind farms in the US. The variable nature of wind makes it difficult to accurately predict how much energy a wind farm could produce in any given time period. But DeepMind states that its AI system— a neural network trained on widely available weather forecasts and historical turbine data — can predict wind power output 36 hours ahead of actual generation with a reasonable degree of accuracy. Based on these predictions, the model recommends how to make optimal hourly delivery commitments to the power grid a full day in advance. This is important because energy sources that can be scheduled (i.e. can deliver a set amount of electricity at a set time) are often more valuable to the grid. Google claims that DeepMind's AI system has boosted the value of its wind energy by roughly 20%. Read More

Image
Image

Healthcare

AI To Predict the Spread of Melanoma

An interdisciplinary team of researchers at Ben-Gurion University of the Negev in Israel and the University of Texas Southwestern Medical Center in Dallas have developed groundbreaking technology to identify melanoma cells that are likely to metastasize to other parts of the body using artificial intelligence (AI). The method is called “quantitative live cell histology”. The technology records video of cells using microscopic cameras and identifies the appearance and behavioural patterns of those cells that have metastatic potential. The group demonstrated that their representation of the functional state of individual cells can predict the likelihood that a stage III melanoma, with malignancies limited to the lymphatic system, will progress to stage IV, in which the cancer has spread from the principal area to the rest of the patient's body. Beyond metastasis prediction potential, the computer models can also distinguish between cancer cells taken from different patients by quantifying factors that are not visible to the naked eye. Read More

Image
Image

Telecommunication

AI to Predict Phone Unlocking, Saving Battery and Bandwidth

Researchers at the University of Melbourne have used machine learning to accurately predict when an individual will next unlock their phone. The technique can be used to trigger more timely data acquisition, better schedule OS updates and synchronisation and improve energy efficiency. The researchers installed an application – a plugin of the AWARE framework, an open-source middleware to capture contextual data on mobile devices – on the phones of 27 Android users over a two-week period. The app collected different sorts of data from the phones, such as light, location, data traffic to app usage, as it could inform the timing of the next ‘unlock event’. Utilising hardware sensors, is in itself, quite energy intensive. So, the researchers repeated their work, using only software-based data. In both cases, the researchers obtained a highly accurate rating for the next ‘unlock event’, with slightly greater accuracy using only software-based data. In 93% of the cases, it accurately predicted whether users would unlock their phone in the next five minutes. Read More

Image
Image

Neuroscience

AI Bring Harry Potter’s Sorting Hat to Life!

Natiliya Kosmyna, a post-doc student at the Massachusetts Institute of Technology (MIT) Media Lab has created a device that can analyse brain activity and sort users into a Harry Potter Hogwarts house. The “Thinking Cap,” a wearable system, is made up of noninvasive electrodes that can capture a person’s brain activity and then uses machine learning to detect and analyse what they’re imagining in real-time. The electrodes are built into a “Sorting Hat” from the Harry Potter franchise, which is equipped with an embedded electroencephalography (EEG) headset and a Bluetooth speaker. For the sorting aspect, Kosmyna first conducts a process called “phase training,” where she shows a participant a series of images and asks them to imagine those objects. The cap will then ask the user a series of binary questions based on the objects Kosmyna showed the student beforehand. And without the participant saying a word, the Thinking Cap will determine which of the two choices the person is thinking about. The answers are then used to determine the Hogwarts house they are best suited for. Read More

Image
Image

Photography

AI-enabled App Aids in Creating Amazing Pics

The Spectre app for Apple’s iOS systems is a long-exposure app that uses AI to simulate what would normally take a long time to capture. Spectre can make moving subjects disappear in busy areas, such as the cars on the bridge below, or you can create light painting and other effects through subject motion, just like when shooting with a DSLR that has been set to a long shutter speed. Spectre doesn't capture a single frame at a long exposure but takes hundreds of frames during the exposure time and merges them. This means you not only get a still image as a final result but also a video. Another cool feature of Spectre is that it can recognize certain types of settings and then apply the appropriate techniques to them such as distinguishing between a beach or a road. Read More

Image
Image

Transport

Now AI Will Aid in Navigating Cities!

Volkswagen AG’s Spanish subsidiary, Seat, has entered into a partnership with International Business Machines Corp, to develop an app that helps people navigate around congested cities. The tool, called Mobility Adviser, will tell customers how to use multiple modes of transport to make crosstown journeys. IBM will supply its Watson AI system needed for the concept to work. The app has no release date and work on it will continue this year, with features such as Facebook profile integration being considered. The app could be released as a standalone utility, integrated into a different piece of Seat software, or made available for third-parties to integrate into their products. Read More

Image
Image

Transport

AI-enabled Cameras to Detect Traffic Rule Offenders

The Motor Vehicles Department (MVD) in Kerala has come up with a new technique to ensure that traffic rule offenders do not go scot free. The department is planning to advance their speed detection cameras by equipping them with AI to detect two wheelers riding without a helmet and four wheel vehicles in which the driver is not wearing a seat belt. The MVD had handed over the tender of this project to the Centre for Development of Advanced Computing, which had undertaken a trial run with the AI installed cameras, during which it was found to be 98% accurate. The AI-enabled cameras have already been installed in many of the cameras in other regions in Walayar, Wadakkanchery and Kozhikode. The software will be introduced soon in all the cameras across the state. Read More

Image
Image

“Quantum Computing, a revolution in technology, has shown great promise towards solving complex computing problems currently outside the capabilities of current computers. Though in its infancy, we at Decimal Point Analytics strongly believe that it is going to grow exponentially in the near future. It holds the potential not only to boost the AI revolution but also transform the way data is synthesized. The articles on Quantum computing will give an insight into the recent developments in this space.”

 
Image

Quantum Computing

Quantum Computing Can Soon Help Secure the Power Grid

The US power grid is at risk from hackers. Oak Ridge and Los Alamos National Labs have been working on a multi-phase project to address this issue with the help of Quantum Key Distribution (QKD). Symmetric Key Encryption systems, often use secure communication in sensor networks, two parties need to exchange a secret key without revealing it to a potential eavesdropper. In local applications, that can often be done by direct exchange. But when the secured system is a distributed network like the power grid, there’s potential for someone to steal the key en-route between nodes. So, a way to guarantee that a received key has not been read by a third party en route would be very valuable. This is where quantum computing comes in. Because the act of reading quantum bits, called qubits, changes them, if data has been read or tampered with on the way, a statistical analysis conducted by the two parties can detect it. This doesn’t guarantee that they’ll have a secure channel, but Quantum Key Distribution (QKD) does guarantee that they’ll know if they’ve indeed been able to securely exchange the needed key. From there, data can be encrypted using whatever protocol is desired. In the demonstration, each of the labs’ systems generated a key, which was sent using QKD to a secure intermediate node. The intermediate node generated a third key that was, in turn, shared privately by the two labs’ endpoints — enabling securely-encrypted data communications to start. Read More

Image
Image

Decimal Point Analytics Pvt Ltd does not make any recommendation, solicitation, or offer for any securities and is not responsible for suitability of any securities for any purpose, investment or otherwise. It is the sole responsibility of the client, as a professional organization, to exercise professional due diligence in ensuring suitability of investment and ensuring that when the client publishes a part or full report under its own brand, the legal requirements for distribution of such material are complied with in all the jurisdiction in which it is published. Decimal Point Analytics Pvt. Ltd. shall not be responsible for any loss suffered by the user. The returns indicated, including future projections, in any investment report prepared by Decimal Point Analytics Pvt Ltd are not guaranteed in any manner and may not be achieved.

India :

5A, B-Wing, Trade Star Building, J. B. Nagar, Andheri-Kurla Road, Andheri (East), Mumbai - 400 059, Maharashtra, India
+91 22 30015200
info@decimalpointanalytics.com

United Kingdom:

1st Floor, 99, Bishopsgate, London, EC2M 3XD, United Kingdom

+ 44 20 3286 1998
info@decimalpointanalytics.com

USA:

17 State Street, Suite 4000, New York, NY 10004 U.S.A

+1 (917) 341 3218
info@decimalpointanalytics.com

www.decimalpointanalytics.com