AI is a consistent point of discussion both in the news and amongst academics and businesses, but what is the ratio of hype to real progress? Billions of dollars are currently being invested in AI and these technologies are progressing faster than ever with self-driving cars, virtual assistants, and robots becoming part of our everyday lives. We heard from some of the leading minds in Machine Intelligence in Amsterdam today who revealed some key progressions in their research. What did we learn, and what did you miss today?
See what Google, DFKI, Scyfer and more had to say.
Topics: Machine Learning, Deep Learning, A I, Robotics
Ride-sharing services are transforming urban mobility by providing timely and convenient transportation to anybody, anywhere, and anytime. Thanks to the global popularity of apps like Lyft and Uber, there are now hundreds of thousands of ride-share drivers, millions of users and billions in VC funding for apps and companies in the industry, despite the dominating companies being only 4-5 years old. But how will autonomous vehicles fit into real-time high-capacity ridesharing?
Topics: Machine Learning, Computer Vision, Smart Transport, Connected Car
As a society, we are increasingly focused on health and wellbeing with influences from the media and influencial professions ever present. This has prompted a huge rise in wearable technologies as a method of keeping track of elements such as activity level and calorie intake. With their built in reminders and personalised features, products such as the Apple Watch, FitBit, and Garmin have opened a new market for technology and fitness.
Fitness apps compatible with the hardware are ever popular, and seemingly being rolled out in abundance. But what makes these fitness products stand out? And how are you supposed to stick to your chosen platform once you’ve signed up?
Topics: Machine Learning, Deep Learning, A I, Healthcare
Following on from our hugely successful Machine Intelligence Summit and Machine Intelligence in Autonomous Vehicles Summit in San Francisco earlier this year, the RE•WORK team are in the final stages of preparation to bring the European edition of this event to Amsterdam this June 28-29. Over the past months the we have been reaching out to the leading minds in machine intelligence to curate a diverse collection of speakers covering a variety of topics.
Topics: Machine Learning, A I, Autonomous Vehicles, Machine Intelligence Summit
Whilst the term ‘augmented reality’ (AR) was coined in the 90s by Boeing researcher Tom Caudell, it’s emergence in customer facing products is still relatively new. Over the past year, numerous smartphone apps have released AR features - think Pokemon Go, Snapchat, and other similar games. These apps allow you to layer a virtual world on top of the real world in front of you. Researchers are currently moving towards embedding AR in everyday life. Whilst the Google Glass didn't receive the acclaim that had been hoped, the technology is there and the ability to disrupt and enhance the world around us with augmented additions is approaching.
With a practical application of AR, L’Oreal have created an app that allows customers to take photographs of themselves and ‘try on’ different products to assess whether they’d be interested in purchasing them.
Topics: A I, Augmented Reality, Virtual Reality, Machine Intelligence Summit
Artificial intelligence is changing our world, and deep learning is a crucial part in attaining this. Deep learning is considered a branch of Machine Learning, with the aim of moving machine learning closer to Artificial Intelligence. It has enabled artificial intelligence to be applied practically, breaking down tasks to help machines understand and perform without being assisted. Advancing the field of deep learning is crucial to progress and breakthroughs within the technology.
Topics: Deep Learning, NLP, Computer Vision, A I
As our Global Deep Learning Summit Series draws closer, we’re casting forward to the three track finale event in San Francisco in January 25 & 26. The sixteenth global Deep Learning Summit will be joined by the first ever Deep Learning for Enterprise Summit as well as the fifth global Virtual Assistant Summit. Deep learning is advancing rapidly and holds great promise for analysing unstructured data, but there are obstacles in its implementation: it’s hard to do, it requires large amounts of data, and it uses a lot of processing power. Pioneers in the industry are working to overcome this, and we are excited to hear from some of the leading industry professionals, academics, startups, and businesses in the field across the three track event.
Topics: Machine Learning, Deep Learning, AI Assistants, Virtual Assistant Summit
As an internationally recognised astrophysicist and the first female Chief Scientist at NASA, and many other outstanding roles in academia at institutions including Stanford, Purdue, Penn State and Cal Tech, France's contributions to science are prolific and widespread. Here she shares the beginnings of her career in science, the biggest breakthroughs we can expect to see in the coming years, and how we can encourage more women and girls into pursuing STEM fields.
Topics: Space, Future of Education , Women in Tech, Ada Lovelace Day
As part of a five year collaboration project, Toyota Research are working with MIT’s Media Lab to build and analyse new deep-learning based perception and motion based planning technologies for autonomous vehicles. Toyota are working with a series of companies specialising in blockchain technology (a distributed database used to maintain a continuously growing list of records that powers the cryptocurrency bitcoin) and are aiming to explore how this can be applied to the industry.
Topics: Machine Learning, Deep Learning, A I, Connected Car
Deep learning is being applied extensively within all the tools that we use in everyday life, mobile phones, computers and even coffee machines. Therefore it is important to understand how the technology works. Over the last few weeks, we have been introducing the A-Z Glossary Series for Deep Learning, which will include explanations for key terms to help build a basic understanding in deep learning.
Topics: Neural Networks, Deep Learning, A I