An algorithm for rubber-banding random points.
To succeed in digital transformation, businesses need to adopt tools that enable collaboration, sharing, and rapid deployment. Jupyter fits that bill.
Ring stacking games. With computers.
A new role focused on creating data products and making data science work in production.
Nothing says machine learning can't outperform humans, but it's important to realize perfect machine learning doesn't, and won't, exist.
The tools of defensive computing, whether they involve mascara and face paint or random autonomous web browsing, belong to the harsh reality we've built.
Is it possible to imagine an AI that can compute ethics?
If behavioral authentication could be made to work, it could be a big part of our future.
It makes no sense at all for programming to be stuck on laptops, but that's where we are.
Machines learn what we teach them. If you don't want AI agents to shoot, don't give them guns.
We need AI researchers who are actively trying to defeat AI systems and exposing their inadequacies.
A framework for thinking about AI.
Is it possible for an AI to create revolutionary art?
Greg Brown's new book, Programming Beyond Practices, is a thoughtful exploration of how software gets developed.
Shared learning: It's what we do at O'Reilly, and it's what we’d like to share with you.
If you look carefully at how humans learn, you see surprisingly little unsupervised learning.
Mike Loukides and Ben Lorica examine factors that have made AI a hot topic in recent years, today's successful AI systems, and where AI may be headed.
A lot can happen in biotechnology with plain old organisms.
Open source has victories, but there are battles that still need to be fought.
Whether our prejudices are overt or hidden, our artificial intelligentsia will reflect them.
Finding patterns isn't really a question about random processes; it's a question about the human brain.
Pete Warden’s instructions on building a deep learning classifier looked so simple, I had to try it myself.
If there's anything humans should learn from AlphaGo, it's that our survival depends on constantly looking at the data.
The "sharing economy" has nothing at all to do with sharing.
A lot of young artists are building brand equity and audience, but fame doesn't equal money and you can't eat brand equity.
The crisis of reproducibility is an opportunity to get better at doing science.
The Programmer's Oath is missing one essential element: the customer.
The revolution in automation is fueling biology at scale.
I don't want barely distinguishable tools that are mediocre at everything; I want tools that do one thing and do it well.
Our fears of automation aren’t due to problems of artificial intelligence, but of human intelligence.
Corporate leadership is as much about building people as it is about developing product.
Building the next generation of leaders, for any size organization.
We need to nurture our imaginations to fuel the biological revolution.
At Cultivate, we'll address the issues really facing management: how to deal with human problems.
It's easy to talk about eliminating hierarchy; it's much harder to do it effectively.
Moving biology out of the lab will enable new startups, new business models, and entirely new economies.
AI scares us because it could be as inhuman as humans.
Cultivate is O'Reilly's conference committed to training the people who will lead successful teams, now and in the future.
Explore how data analysis will help us structure the business of health care more effectively around outcomes, and personalize medicine for each specific patient.
Empathy, communication, and collaboration across organizational boundaries.
What the future of science will look like if we’re bold enough to look beyond centuries-old models.
How the IoT is revolutionizing not just consumer goods and gadgets, but manufacturing, design, engineering, medicine, government, business models, and the way we live our lives.
BioCoder 6: iGEM's first Giant Jamboree, an update from the #ScienceHack Hack-a-thon, the Open qPCR project, and more.
A look at what lies ahead in the disenchanted age of postmodern computing.
Biological products have always seemed far off. BioFabricate showed that they're not.
Uber has built a great service. Why do they feel the need to use dirty tricks to succeed?
We need to understand our own intelligence is competition for our artificial, not-quite intelligences.
Is the unemployment problem about a lack of qualified applicants in the workforce?
The data that drives products is shifting from overt to covert.
The future belongs to the companies and people that turn data into products.