AMSTERDAM and SAN FRANCISCO, Oct. 16, 2019 – Databricks, the leader in unified data analytics, today announced Model Registry, a new capability within MLflow, an open-source platform for the machine learning (ML) lifecycle created by Databricks. The new component enables a comprehensive model management process by providing data scientists and engineers a central repository to track, share, and collaborate on machine learning models. The Model Registry manages the full lifecycle of models and their stage transitions from experimentation to staging and deployment. Since introducing MLflow at Spark AI Summit 2018, the project has more than 140 contributors and 800,000 monthly downloads making it the leader in ML lifecycle management. "Everyone who has tried to do machine learning development knows that it is complex. The ability to manage, version and share models is critical to minimizing confusion as the number of models in experimentation, testing and production phases at any given time can span into the thousands," said Matei Zaharia, co-founder and CTO at Databricks.

SAS announced a $1 Billion investment in AI a few months ago. We sat down with Iain Brown, Head of Data Science at SAS to discuss the challenges and opportunities of AI in enterprises. He also discusses how ethics and good AI is'tricky' and requires a carefully thought out framework in order to succeed. Iain: Certainly, I have always had a fascination in the practical applications of mathematics, statistics as well as a love for computer science. So the rise of Data Science as a professional vocation was the perfect fit.

Email marketing is often misunderstood. When people ask me what I do and I tell them I'm an email marketing specialist, the first (and most frequent) response I get is "Oh, so you send all those spam emails? Or "Oh, so you just send emails all day? I wish that's all I had to do." This is annoying for a number of reasons, but mostly because it seems that no one really appreciates (or understands) the effort that goes into making a good email.

According to an article published last week to the journal of Soft Robotics, scientists based out of the Swiss Federal Institute of Technology Lausanne in Lausanne, Switzerland, have developed a skin-like material that, when worn over a users' body, simulates a far more realistic sense of touch than that of current haptic feedback technologies. Referred to as "Closed-Loop Haptic Feedback Control Using a Self-Sensing Soft Pneumatic Actuator Skin," the device is composed of a stretchable material only 500 nanometers thick, allowing it to form to a users body. Lined with a series of pneumatic actuators, the ultra-compliant thin-metal film strain sensor creates a highy-realistic tactile sense via vibratory feedback. Put simply, the "skin" uses pressure triggered by inflated membranes to create a sense of touch far more realistic than that of current haptic feedback solutions, which rely primarily on mechanical vibration technology to replicate a sense of impact. This layer of membrane can be altered to various pressures and frequencies by pumping air into it; deflating and inflating the membrane rapidly will cause the skin to vibrate.

The advance of emerging technologies enabled by cloud computing has been dizzying over the last several years. In some cases, these new technologies have been created by cloud companies specifically for the cloud; for instance, serverless. In other cases, a technology has advanced by its close relationship with the cloud; for instance, machine learning and artificial intelligence. In either case, these emerging technologies are changing not just cloud, but the larger world of enterprise computing – not to mention sectors ranging from retail to media to pharmaceutical. These emerging technologies – either cloud-based or highly interoperable with the cloud – offer enormous promise, yet they have also contributed to a growing complexity in cloud computing.

AI is quickly becoming an important part of our lives, whether that's in your personal life or at work. Most of us are using AI every day, often without realising. It helps us sort our emails, automatically removing spam from our inbox. It gives us personalised recommendations when shopping, assists us when parking cars and can even translate languages in real time. AI can collect and analyse data faster than any human, but it's not designed to replace us.

Data on the effectiveness of the artificial intelligence screening system EyeArt was presented at the American Academy of Ophthalmology (AAO) 2019 Annual Meeting in San Francisco. Results of the study examining EyeArt revealed the system had the ability to accurately predict diabetic retinopathy 95.5% of the time, without the input of an ophthalmologist, and in less than a minute. With the diabetes epidemic continuing to plague patient populations in the US and across the globe--and 1 in 4 diabetics developing diabetic retinopathy--investigators sought to evaluate the effectiveness of the artificial intelligence screening system in a group of 893 patients. Led by Srinivas Sadda, MD, of the Doheny Eye Institute at UCLA, investigators conducted the study at 15 different centers across the US. For inclusion in the study, patients needed to have a diagnosis pf diabetes mellitus, be at least 18 years of age, and provide written informed consent.

Healx has raised $56 million (€51 million) to launch 40 rare disease programs while taking some of its existing assets into the clinic. The ambitious target is enabled by an AI drug discovery platform that Healx thinks gives it a scalability that has more in common with tech than biotech. David Brown, the former global head of drug discovery at Roche, and Tim Guilliams cofounded Healx in 2014 to use AI to find opportunities to repurpose existing molecules to treat rare diseases. After quietly working on the technology in its early years, Healx raised $10 million last year to build on its early success in identifying a potential treatment for Fragile X syndrome. That money was due to see Healx through to 2020 but Guilliams, who works as CEO, decided to pull the financing forward in light of the success rate of the company's predictions and translations.

Dozens of platform updates, additional AI-driven functionality, and new products to help you optimize, implement, and measure more automations. Uncovers efficiencies and provides insights, making the path to digital transformation fast and cost-effective. It leverages systems to minimize disruption. By automating tasks, your teams are free to spend time on work with better returns. Marketplace give your employees more time--in less time.

The treatment of mental health conditions appears to have received a boost with a recently announced research collaboration between digital mental health company SilverCloud Health and Microsoft Research. The partnership was designed to further step up the former's online offering with artificial intelligence. A little background: During the past 18 months, the two have worked in tandem on research that marries Microsoft's machine learning and AI technologies with SilverCloud, which specializes in the digital delivery of evidence-based mental healthcare to improve outcomes. Ken Cahill, CEO of Boston based SilverCloud, said the technology enables "very tailored support" to each patient; meaning "more responsive and reactive care." He called that process a "big departure" from existing digital delivery that's generic or a one-size-fits-all approach and doesn't accommodate for factors such as behavior, engagement, and effectiveness.