It’s time to address the reproducibility crisis in AI

 

GUEST: Recently I interviewed Clare Gollnick, CTO of Terbium Labs, on the reproducibility crisis in science and its implications for data scientists. The podcast seemed to really resonate with listeners (judging by the number of comments we’ve received via the show notes page and Twitter), for several reasons. To sum up the issue: Many resear…Read More

Improving AI Systems with Human Feedback and no Heartburn

Humans play an indispensable role in many modern AI-enabled services – not just as consumers of the service, but as the actual intelligence behind the artificial intelligence. From news portals to e-commerce websites, it is people’s ratings, clicks, and other interactions which provide a teaching signal used by the underlying intelligent systems to learn. While these human-in-the-loop systems improve through user interaction over time, they must also provide enough short-term benefit to people to be helpful. Continue reading “Improving AI Systems with Human Feedback and no Heartburn”

Getting Linked In to Data Science with Dr. Igor Perisic

Dr. Igor Perisic – Chief Data Officer

Episode 11, February 7, 2018

Getting Linked In to Data Science with Dr. Igor Perisic

Big data is a big deal, and if you follow the popular technical press, you’ll have heard all the metaphors: data is the new oil, the new bacon, the new currency, the new electricity. It’s even been called the new black. While data may not actually be any of these things, we can say this: in today’s networked world, data is increasingly valuable, and it is essential to research, both basic and applied. Continue reading “Getting Linked In to Data Science with Dr. Igor Perisic”

The new podcast is here, and just in time for your commute. Don’t miss a chance to hear from Ruth Pickering about how @DoYewno is helping others uncover the undiscovered faster with AI and neural networking. https://blog.outsellinc.com/uncovering-the-undiscovered-faster-with-ai-and-neural-networking-e02eb28dc1b3 …

The new podcast is here, and just in time for your commute. Don’t miss a chance to hear from Ruth Pickering about how is helping others uncover the undiscovered faster with AI and neural networking. https://blog.outsellinc.com/uncovering-the-undiscovered-faster-with-ai-and-neural-networking-e02eb28dc1b3 …

How the practice of design enhances artificial intelligence

Artificial Intelligence (AI) systems can perform amazing feats of problem-solving. But no matter how accurate AI solutions are, they won’t be relevant, insightful and adopted by people without great design work.

The practice of design is about problem solving. It starts long before the visual look and feel is created and continues long afterward. It creates a vital connection between humans and machines that allows AI systems to perform at their best.

In this article, I’ll focus on discrete cognitive machine tools and systems built for specific tasks, rather than Artificial General Intelligence. Continue reading “How the practice of design enhances artificial intelligence”

Can AI Win the War Against Fake News?

Developers are working on tools that can help spot suspect stories and call them out, but it may be the beginning of an automated arms race.

“Testing a demo version of the AdVerif.ai, the AI recognized the Onion as satire (which has fooled many people in the past). Breitbart stories were classified as “unreliable, right, political, bias,” while Cosmopolitan was considered “left.” It could tell when a Twitter account was using a logo but the links weren’t associated with the brand it was portraying. AdVerif.ai not only found that a story on Natural News with the headline “Evidence points to Bitcoin being an NSA-engineered psyop to roll out one-world digital currency” was from a blacklisted site, but identified it as a fake news story popping up on other blacklisted sites without any references in legitimate news organizations.”

Tracking a Descent to Savagery with the Wolfram Language: Plotting Sentiment Analysis in Lord of the Flies

Computation is no longer the preserve of science and engineering, so I thought I would share a simple computational literary analysis that I did with my daughter.

Shell Lord of the Flies

 

Hannah’s favorite book is Lord of the Flies by William Golding, and as part of a project she was doing, she wanted to find some quantitative information to support to her critique. Continue reading “Tracking a Descent to Savagery with the Wolfram Language: Plotting Sentiment Analysis in Lord of the Flies”

Fact-Checking Software Detects Genetic Errors in Cancer Research Publications

In early October, two scientists shared a software program that detects incorrect gene sequences in already published research experiments. Using the program, the duo identified experimental flaws in more than 60 papers within cancer research alone. Scientists Jennifer Byrne and Cyril Labbé combined their expertise in cancer-research and computer-science, to introduce the software “Seek &…
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‘Contextual bandit’ breakthrough enables deeper personalization

Microsoft senior researcher Miro Dudík.

News portals that simultaneously personalize every part of the landing page for every visitor and mobile health apps that adaptively tweak every part of an exercise regimen to maximize the benefit of every user are becoming plausible due to an advance in a type of interactive machine learning that my team will describe at the Annual Conference on Neural Information Processing Systems running December 4-9 in Long Beach, California. Continue reading “‘Contextual bandit’ breakthrough enables deeper personalization”

Tech giants are using open source frameworks to dominate the AI community


Tech giants such as Google and Baidu spent from $20 billion to $30 billion on AI last year, according to the recent McKinsey Global Institute Study. Out of this wealth, 90 percent fueled R&D and deployment, and 10 percent went toward AI acquisitions.

Research plays a crucial role in the AI movement, and tech giants have to do everything in their power to seem viable to the AI community. AI is mostly based on research advances and state-of-the-art technology, which is advancing very quickly. Therefore, there is no business need to make closed infrastructure solutions, because within a few months everything will be totally different.

In such a situation, the only winning strategy for tech giants is to offer open source solutions to attract members of the AI community and eventually become part of the AI community themselves. This is a relatively new model in the tech industry. Continue reading “Tech giants are using open source frameworks to dominate the AI community”

paper published in arXiv by researchers from Stanford describes a deep neural network that can look at a patient’s records and estimate the chance of mortality in the next three to 12 months. The team found that this serves as a good way to identify patients who could benefit from palliative care. Importantly, the algorithm also creates reports to explain its predictions to doctors.

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