Summary: Computational Synthetic Biology (CSB) is likely to be both the next big thing and perhaps most important field to exploit data science. As the name implies, this lies at the intersection of data science and biological research. Big advancements and big investments are already starting to occur here. Data scientists with deep learning skills will want to check this out.
Added by William Vorhies on June 19, 2018 at 7:55am — No Comments
Summary: Data Science is the secret sauce that turns the dumb internet into the smart internet driving changes in society as fast as we drive changes in the internet. The best place to find data on this is Mary Meeker’s Internet Trend Report 2018. Here we use that data to look back at the last year and forward a bit in time to see what impact data science is having.
Added by William Vorhies on June 12, 2018 at 8:30am — No Comments
Not quite ready for world domination! 'Suicidal' security robot drowns itself in a fountain
A security robot created by the company Knightscope was patrolling an…Continue
Summary: There is a great hue and cry about the danger of bias in our predictive models when applied to high significance events like who gets a loan, insurance, a good school assignment, or bail. It’s not as simple as it seems and here we try to take a more nuanced look. The result is not as threatening as many headlines make it seem.
Added by William Vorhies on June 5, 2018 at 8:00am — No Comments
Summary: Researchers in Synthetic Neuro Biology are proposing to solve the AGI problem by building a brain in the laboratory. This is not science fiction. They are virtually at the door of this capability. Increasingly these researchers are presenting at major AGI conferences. Their argument is compelling.
Added by William Vorhies on May 21, 2018 at 3:00pm — No Comments
Summary: The annual Burtch Works study of Data Science salaries and employment statistics is just out and things continue to look great. There are some interesting trends here you’ll want to know about.
Summary: Before starting to develop an AI strategy, make sure your team understands the limits of what is reasonable today, as well as incremental improvements that might be overlooked. Focus should be on your LOB leaders who understand the business. Make sure they are also able to recognize AI opportunities.
Added by William Vorhies on May 8, 2018 at 9:59am — No Comments
Summary: Our starting assumption that sequence problems (language, speech, and others) are the natural domain of RNNs is being challenged. Temporal Convolutional Nets (TCNs) which are our workhorse CNNs with a few new features are outperforming RNNs on major applications today. Looks like RNNs may well be history.
Summary: Not everyone wants to invest the time and money to become a data scientist, and if you’re mid-career the barriers are even higher. If you still want to be deeply involved in the new data-driven economy and well paid, the growth rate and opportunities as a data engineer or business analyst need to be on your radar screen.
Summary: Deep Learning, based on deep neural nets is launching a thousand ventures but leaving tens of thousands behind. Transfer Learning (TL), a method of reusing previously trained deep neural nets promises to make these applications available to everyone, even those with very little labeled data.
Added by William Vorhies on April 17, 2018 at 12:25pm — No Comments
Summary: There are several things holding back our use of deep learning methods and chief among them is that they are complicated and hard. Now there are three platforms that offer Automated Deep Learning (ADL) so simple that almost anyone can do it.
Summary: Automated Machine Learning has only been around for a little over two years and already there are over 20 providers in this space. However, a new European AML platform called Tazi, new in the US, is showing what the next generation of AML will look like.
Added by William Vorhies on April 3, 2018 at 7:30am — No Comments
Summary: GDPR carries many new data and privacy requirements including a “right to explanation”. On the surface this appears to be similar to US rules for regulated industries. We examine why this is actually a penalty and not a benefit for the individual and offer some insight into the actual wording of the GDPR regulation which also offers some relief.
Summary: We’re stuck. There hasn’t been a major breakthrough in algorithms in the last year. Here’s a survey of the leading contenders for that next major advancement.
Summary: Some observations about new major trends and directions in data science drawn from the Strata Data conference in San Jose last week.
Summary: A major problem with chatbots is that they can only provide information from what’s in their knowledge base. Here’s a new approach that makes your chatbot smarter with every question it can’t answer, making it a self-learning lifelong…Continue
Summary: The Magic Quadrant for Advanced Analytic and ML Platforms is just out and there are some big changes in the leaderboard. Not only are there some surprising upgrades but some equally notable long falls.
The Gartner Magic Quadrant for Advanced Analytic and ML Platforms came out on February 22nd and there are some big changes in the leaderboard. Not only are there some surprising upgrades (Alteryx, KNIME, H20.ai) but some…Continue
Summary: This is the second in our “Off the Beaten Path” series looking at innovators in machine learning who have elected strategies and methods outside of the mainstream. In this article we look at Numenta’s unique approach to scalar prediction and anomaly detection based on their own brain research.
Added by William Vorhies on February 20, 2018 at 8:30am — No Comments
Summary: How about a deep learning technique based on decision trees that outperforms CNNs and RNNs, runs on your ordinary desktop, and trains with relatively small datasets. This could be a major disruptor for AI.
Summary: There are an increasing number of larger companies that have truly embraced advanced analytics and deploy fairly large numbers of data scientists. Many of these same companies are the one’s beginning to ask about using AI. Here are some observations and tips on the problems and opportunities associated with managing a larger data science function.