Over the past year, we've had the pleasure of welcoming a number of leading Machine Learning (ML) focused companies to the Notion family. These are startups that are tackling verticals ranging from autonomous vehicles (Five.AI) to behavioural monitoring within the enterprise (Status Today). What's more, many of our existing portfolio companies are now using ML to power aspects of their products and delivering accelerating returns as they go. As a B2B fund with a strong history in SaaS, we keep an eye out for emerging technologies that have the potential to bring a business's marginal cost down to near-zero and in turn, enable subscription-based models. Here are a few thoughts on why we are bullish about a new wave of AI startups and the lens through which we are analyzing these opportunities.

The polls have consistently showed Hillary Clinton with a lead over Donald Trump in recent weeks, but an artificial intelligence system has a different prediction for the outcome of the presidential election. The system, called MogIA, uses 20 million data points from online platforms like Google, YouTube, and Twitter to come up with its predictions, according to CNBC. MogIA correctly predicted the past three presidential elections as well as the Democratic and Republican primaries. "While most algorithms suffer from programmers/developer's biases, MoglA aims at learning from her environment, developing her own rules at the policy layer and develop expert systems without discarding any data," Sanjiv Rai, the founder of Indian start-up Genic.ai MogIA uses data such as engagement with tweets and videos posted to the platforms the system looks at.

IBM Aims Watson at Embodied Cognition By Darryl K. Taft Posted 2016-11-05 Print Q&A: IBM is focusing its Watson cognitive computing technology on the area of embodied cognition, according to Grady Booch, chief scientist of Watson/M. At the close of IBM's recent World of Watson conference in Las Vegas, eWEEK interviewed Grady Booch, Big Blue's chief scientist of Watson/M about the future of IBM's Watson cognitive computing platform and where IBM is taking the technology to benefit enterprise customers, consumers and developers alike. Among other areas, IBM is applying Watson to embodied cognition or putting artificial intelligence (AI) into the physical world. "This is embodied cognition: By placing the cognitive power of Watson in a robot, in an avatar, an object in your hand or even in the walls of an operating room, conference room or spacecraft, we take Watson's ability to understand and reason and draw it closer to the natural ways in which humans live and work," Booch said in a talk. "In so doing, we augment individual human senses and abilities, giving Watson the ability to see a patient's complete medical condition, feel the flow of a supply chain or drive a factory like a maestro before an orchestra."

John Rampton is founder of online invoicing company Due. By now everyone has heard of Google's RankBrain, the new artificial intelligence machine learning algorithm that is supposed to be the latest and greatest from Mountain View, Calif. What many of you might not realize, however, is just how fast the SEO industry is changing because of it. In this article, I'll take you through some clear examples of how some of the old rules of SEO no longer apply, and what steps you can take to stay ahead of the curve in order to continue to provide successful SEO campaigns for your businesses. So what is artificial intelligence?

Scientists at Oxford University have developed a machine that can lip-read better than humans. The artificial intelligence system – LipNet – watches video of a person speaking and matches the text to the movement of their mouths with 93% accuracy, the researchers said. They suggested, automating the process could help millions. But experts say that more testing in real-life situations are needed to fully understand the benefits. Lip-reading is a notoriously tricky with professionals only able to decipher what someone is saying around 60% of the time.

Facebook has begun allowing businesses to send users adverts on Messenger, but only if those users have previously made contact with the brand. Part of Facebook's iteration of its Messenger chat service as a platform, announced at Web Summit in Lisbon, the change will mean that if a user ever contacts a brand that will open the door to that brand then sending them adverts through the instant messaging app. "Sponsored messages" as Facebook calls them provides another revenue opportunity for Facebook, targeting users in a place where they are less likely to automatically screen out adverts. David Marcus, Facebook's vice president of messaging, said: "Of course, people using Messenger shouldn't worry about getting spammed, because the starting principles still remain: businesses can't send a sponsored message to threads that weren't previously opened by their customers or prospects, and users have full control to block messages or people/businesses they no longer want to hear from." However, users wanting to avoid ads will have to be careful which brands, chatbots and other interfaces within Messenger they use. If a user messages a chatbot it gives that brand carte blanche to then send the user adverts.

The meetup will be hosted by AAA-data / Comité des Constructeurs Français d'Automobiles and the networking event is sponsored by Zen.ly . A big thank you to them. The program for this third regular meetup of the season (and the fifth total for season 4) is a little extraordinary this time and will feature the following: Dominique Gillot, Sénatrice, ancienne ministre et Rapporteure avec le député Claude de Ganay d'un rapport sur l'Intelligence Artificielle pour le Parlement. Julien Simon (Amazon), Machine Learning & Deep Learning with Amazon Web Services Gautier Marti (Hellebore Capital), A closer look at correlations You may have already read many times that the job of a Data Scientist is to skim through a huge amount of data searching for correlations between some variables of interest. And also, that one of his worst enemies (besides correlation doesn't imply causation) is spurious correlation.

Chainer is an open source framework designed for efficient research into and development of deep learning algorithms. In this post, we briefly introduce Chainer with a few examples and compare with other frameworks such as Caffe, Theano, Torch, and Tensorflow. Most existing frameworks construct a computational graph in advance of training. This approach is fairly straightforward, especially for implementing fixed and layer-wise neural networks like convolutional neural networks. However, state-of-the-art performance and new applications are now coming from more complex networks, such as recurrent or stochastic neural networks. Though existing frameworks can be used for these kinds of complex networks, it sometimes requires (dirty) hacks that can reduce development efficiency and maintainability of the code.

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You might expect the operating theatre to be one of the last places you'd find robotics in action but, increasingly, you'd be wrong. The OT is typically the most labour-intensive and expensive part of a hospital -- which, in this age of spiraling health costs, makes it a priority for any cost-savings that can be achieved through systemisation and standardisation. Robotic surgery, or robot-assisted surgery, has the advantage that it allows doctors to perform many types of complex procedures with more precision, flexibility and control than they could with conventional techniques. Given the speed at which robotics is advancing, how long will it be before robots start making all the decisions on surgery without the need for human control or intervention? OK, you say, that's fine where standard and predictable procedures are required.