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Ajay Royyuru and Guillermo Cecchi from IBM Healthcare join Chris and Daniel to discuss the emerging field of computational psychiatry. They talk about how researchers at IBM are applying AI to measure mental and neurological health based on speech, and they give us their perspectives on things like bias in healthcare data, AI augmentation for doctors, and encodings of language structure.
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Fully Connected – a series where Chris and Daniel keep you up to date with everything that’s happening in the AI community.
This week we look back at 2018 - from the GDPR and the Cambridge Analytica scandal, to advances in natural language processing and new open source tools. Then we offer our predications for what we expect in the year ahead, touching on just about everything in the world of AI.
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2018 in Review
Predictions for 2019
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Susan Etlinger, an Industry Analyst at Altimeter, a Prophet company, joins us to discuss The AI Maturity Playbook: Five Pillars of Enterprise Success. This playbook covers trends affecting AI, and offers a maturity model that practitioners can use within their own organizations - addressing everything from strategy and product development, to culture and ethics.
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Fully Connected – a series where Chris and Daniel keep you up to date with everything that’s happening in the AI community.
This week we discuss all things inference, which involves utilizing an already trained AI model and integrating it into the software stack. First, we focus on some new hardware from Amazon for inference and NVIDIA’s open sourcing of TensorRT for GPU-optimized inference. Then we talk about performing inference at the edge and in the browser with things like the recently announced ONNX JS.
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Joe Doliner (JD) joined the show to talk about productionizing ML/AI with Pachyderm, an open source data science platform built on Kubernetes (k8s). We talked through the origins of Pachyderm, challenges associated with creating infrastructure for machine learning, and data and model versioning/provenance. He also walked us through a process for going from a Jupyter notebook to a production data pipeline.
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Fully Connected – a series where Chris and Daniel keep you up to date with everything that’s happening in the AI community.
This week we discuss BERT, a new method of pre-training language representations from Google for natural language processing (NLP) tasks. Then we tackle Facebook’s Horizon, the first open source reinforcement learning platform for large-scale products and services. We also address synthetic data, and suggest a few learning resources.
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We recently met up with Cormac Brick (Intel) and Mike Del Balso (Uber) at O’Reilly AI in SF. As the director of machine intelligence in Intel’s Movidius group, Cormac is an expert in porting deep learning models to all sorts of embedded devices (cameras, robots, drones, etc.). He helped us understand some of the techniques for developing portable networks to maximize performance on different compute architectures.
In our discussion with Mike, we talked about the ins and outs of Michelangelo, Uber’s machine learning platform, which he manages. He also described why it was necessary for Uber to build out a machine learning platform and some of the new features they are exploring.
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Brett Gaylor joins Chris and Daniel to chat about the recently announced winners of Mozilla’s creative media awards, which focuses on exposing the impact of AI on society. These winners include a film that responds to the audience (via AI recognized emotions) and an interesting chatbot called Wanda.
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Himani Agrawal joins Daniel and Chris to talk about how she got into data science and artificial intelligence, and offers advice to others getting into these fields. She goes on to describe the role of artificial intelligence and machine learning within AT&T and telecom in general.
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In this new and updates show, Daniel and Chris discuss, among other things, efforts to use AI in art and efforts to make AI interfaces look human. They also discuss some learning resources related to neural nets, AI fairness, and reinforcement learning.
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