A guide to protecting AI and machine learning inventions


Securing patents for inventions that use artificial intelligence (AI) and machine learning can be challenging for innovators of these ground-breaking technologies, which attempt to use the processing power of computers to replicate the intelligence and learning capabilities of humans. Without patent or other intellectual property protection, they may be unable to commercialise their inventions, which could undermine investment in this dynamic field of research and development. To clear the way for innovators, the European Patent Office has recently amended its'Guidelines for Examination' by including a new section containing advice about how patents related to AI and machine learning technologies should be assessed. The guidance clarifies that whilst algorithms are regarded as'computational' and abstract in nature, which means they are not patentable per se, once applied to a technical problem they may become eligible for patent protection. Beneficially, the approach outlined in the guidance is similar to that currently used to assess the patentability of computer-implemented inventions.

Google's new Conversion Probability metric Smart Insights


I'm reviewing a different type of Chart today since while reviewing Google's Demo Account while working on some new learning materials for our members I noticed the intriguing new Conversion Probability feature Beta. Here's what it shows for the one hundred thousand odd sessions in the Demo account: You can see that it breaks down these sessions into likelihood to convert, so if we can learn more about what turns the high-converting visitors onto our products, we have more chance of finding and converting more visits in future. As we explain in our AI and machine learning guide, for us, the most exciting marketing application of artificial intelligence is using machine learning to learn from historic interactions with our audiences see what influences their propensity to convert. Using this insight we can tailor our communications to be more relevant. Here, Google analyses historic visits of sites which have at least 1,000 e-commerce transactions to see which of all the variables available in analytics like visitor source, content consumed and path determine propensity to purchase.

AI start-ups huddle


AI start-ups Crossbar, Gyrfalcon Technology, Neural Networks Corporation and Robosensing are getting together to deliver an AI platform and standard for edge computing, gateways, cloud and data centers. The group, called SCAiLE (SCalable AI for Learning at the Edge), is already working with Japanese authorities to review opportunities for the 2020 Olympics, including video-based event detection and response capability. The organization will combine advanced acceleration hardware, resistive memory (ReRAM), optimized neural networks to create ready-made, power-efficient solutions with unsupervised learning and event recognition capability. The consortium addresses the restrictions of traditional AI methodologies that depend on classification of data. The huge growth of IoT systems including thousands of remote edge devices such as sensor-equipped cameras creates a torrent of unstructured information in multiple forms that pours into cloud-located servers and that cannot be handled effectively by classification alone.

Can a machine outsmart a human? Artificial intelligence goes up against debate champion


In a packed auditorium in San Francisco on Monday night a competition of man versus machine took place. In this case, man won. A grand finalist at the 2016 World Debating Championship took up the challenge of a live debate against an artificial intelligence machine in front of an audience of thousands. Harish Natarajan, 31, from London took on IBM's latest AI machine following the Watson Project. Project Debate, which resembles a tall speaker with a small screen, has been developed over the course of seven years by a team of dozens of people in multiple countries including Israel and India.

Podcast: What is an Ai Supercomputer? - insideHPC


The HPE SGI 8600 platform will be the core component of the Jean Zay Aiu supercomputer in France. In this podcast, the Radio Free HPC team asks whether a supercomputer can or cannot be a "AI Supercomputer." The question came up after HPE announced a new AI system called Jean Zay that will double the capacity of French supercomputing. So what are the differences between a traditional super and a AI super? According to Dan, it mostly comes down to how many GPUs the system is configured with, while Shahin and Henry think it has something to do with the datasets.

How to Control AI that Becomes Too Advanced?


Artificial Intelligence is rapidly becoming more advanced. One of the organisations working on AI is OpenAI; the not-for-profit artificial intelligence research organisation co-founded by Elon Musk. Last week, they produced a paper demonstrating the progress they have made on predictive text software. The AI that they developed, called GPT2, is so efficient in writing a text based on just a few lines of input, that OpenAI decided not to release the comprehensive research to the public. Already, GPT2 has been described as the text version of deep fakes.

Investment in UK artificial intelligence startups soars


Venture capital (VC) investment in the UK's growing artificial intelligence (AI) sector leapt almost six-fold from 2014 to 2018, with funding comprising almost as much as the rest of Europe combined. According to research prepared for Tech Nation and the Digital Economy Council by Dealroom, investment in UK AI startups reached US$ 1.3 billion in 2018. Notable deals in 2018 included Bristol-based Graphcore which raised US$200m. Throughout 2018, Dealroom recorded 82 venture capital fundraisings across UK companies, compared to 70 in the previous year-- that's a continuation of a trend that's seen investment in AI companies grow sharply over the last five years. "These statistics are further confirmation that the UK is Europe's undisputed number one tech hub," said the UK digital secretary, Jeremy Wright.

Think you can tell between a real and computer-generated face? This website will test you.


So you might've been a bit freaked out about those extremely realistic, computer generated faces. Could you tell they were fake? Now, you can put yourself to the test with a website called SEE ALSO: This website uses AI to generate faces of people who don't exist It's a simple quiz to determine if you're good at telling the difference between a real human face and one created by an artificial intelligence algorithm. The fake faces are generated by StyleGAN, an algorithm by Nvidia researchers designed to create artificial images that are indistinguishable from real photographs.

How AI and Machine Learning Are Developing Smarter Football Coaching Analytics Insight


It is not uncommon nowadays for teams at every professional level to have an analytics department, and to have coaching staff that rely on analytics to make informed decisions. Here on we touched on the rise of sports analytics in a previous post, where we defined it as the use of data to build predictive models for informed decision making. Now, imagine sports analytics today. Then throw in artificial intelligence (AI), into the mix. The results are a system in which massive data sets can be analysed quickly and accurately.