Huge amounts of data are available via e-commerce, allowing retailers to create deep learning algorithms that can follow the customer journey to help optimize search results, targeted advertising and predict the types of purchases customers are likely to make. The e-commerce sites are then able to serve suggestions to users based on their previous search and purchase history taking into account several factors such as location, previous website activity and any other information the system may have access to such as age and gender.
Topics: Machine Learning, Deep Learning, A I, Deep Learning Summit
By now, most industries understand the value of social media platforms. Being an influencer in your space and gaining trust from your potential customers equals growth, new business, and increased profits. It’s also widely acknowledged that social media management is time consuming and as a result can often get left behind or be executed poorly.
This week at the Deep Learning Summit in London, Antoine Amann from Echobox will explain how he has built a platform to alleviate this stress for publishers by building a platform that intelligently posts articles on social media. The AI can take over the entire logistics of content distribution by automatically creating and posting material to share on social media.
Topics: Big Data, Machine Learning, Deep Learning, NLP
Deep learning algorithms are now transiting from proof-of-concepts or academic research to production deployments in industry. Businesses may be keen to apply AI to their work, but unable to execute the strategies due to lack of funding, staff, or knowledge within their teams. This, however, should not be seen as an obstacle for smaller businesses, and Intel’s Nervana Cloud that enables businesses to develop custom deep learning software. Intel Nervana offer their deep learning expertise, coupled with a deep learning platform that enables data scientists to schedule training jobs, track their experiments, and test deployment plans.
Topics: Deep Learning, Cloud Computing, A I, Deep Learning Summit
The big question on the tip of everyone’s tongues: are these non-human virtual assistants about to steal our jobs? The answer, in short - is no. AI assistants are being created to help and enhance their human counterparts making us more efficient, and helping us optimise our time and resources. The sole purpose of AI is not to produce the same product cheaper and faster - they want to offer better products, customer service, and superior user experiences.
Topics: Future of Education , Machine Learning, Deep Learning, AI Assistants
How do you go about transforming a 100+ year old auto company with over 120,000 employees from their traditional methods into the digital, artificially intelligent way of thinking?
This is the challenge Renault are currently facing, and one that led to the launch of Renault Digital that started its operations on January 1st of this year and is aimed at digitalising Renault ‘s core business for it’s employees, partners and clients worldwide, working to build tomorrow’s digital abilities and scope.
Topics: Machine Learning, Deep Learning, A I, Connected Car
The landscape of deep learning is constantly evolving. The training of DL models has come a long way from Yann LeCun's combining of convolutional neural networks with recent backpropagation theories to read hand-written codes in 1989, a model which took an impractical 3 days to train. (LeCun et al., 1989) From initial experiments in training models to play games and recognize basic shapes and images, the AI has matured into a tool positively impacting and disrupting society across multiple industries.
Deep learning is not just for 'tech companies'! Find out which industries are leveraging AI to optimize their returns and efficiency.
Topics: Machine Learning, Deep Learning Algorithms, Deep Learning, A I
Chief Information Officers are the rulers of corporate data. They are responsible for picking the right data to process into information, and then squeezing out meaning that will drive business forward. And the way they do this is about to change.
CIOs have done their job under a command and control paradigm. Their number crunching machines, no matter how sophisticated, can only do exactly what they are told.
Topics: Deep Learning, Pattern Recognition, A I, Deep Learning Summit
Wouldn’t it be great to have a personal assistant to help you with all your insurance needs. SPIXII is exactly this - the chatbot that wants to make your customer service experience easier, more efficient, and more human. The word ‘insurance’ is enough to put most people off, evoking painful memories of long forms, waiting on hold listening to terrible lift music, and eventually being oversold on a policy you don’t really need.
SPIXII’s goal is to ‘build a bridge between customers and insurers’ through the implementation of an AI powered chatbot.
Topics: AI Assistants, A I, Financial Compliance, Chatbots
You hear this all the time. You’re starting a business and you get told it’s probably going to fail. Whilst this is a very real possibility and one that is true nine times out of ten, there’s still that 10% that not only succeed in making a profit, but go on to get acquired by huge corporations or secure large rounds of funding.
With AI advancing at groundbreaking speed, an increasing number of players entering the race are startups who have been acquired by the likes of Microsoft, Google, Twitter, Apple and other huge names. At every RE•WORK summit we welcome thriving startups and learn about their advances in AI, so we’re taking a look to see where some of them are now.
Topics: Machine Learning, Deep Learning, Startups, AI Assistants
“Do I need to take a coat today?”, “Play my workout playlist in the living room”, “Order me a takeaway.” Demands that your family might find pretty rude or tiresome, but perfectly acceptable to ask your voice and chat assistant. But we all know how frustrating these AI Assistants have previously been - you ask your phone to “Call Mom” and are answered with “Searching Google for Mom” - argh, no! We shouldn’t be to surprised, however, that the first generation of these assistants didn’t behave in the way we wanted them to. We were expecting our smartphones and household devices to understand our accents, colloquialisms, and emotions in the same way a human brain processes these types of information, when that is something that the machine simply cannot comprehend.
Topics: Voice Recognition, NLP, AI Assistants, Virtual Assistant Summit