We welcome written submissions from individuals and organisations who are developing policy, systems or safeguards on the use of AI as we gather evidence for this review. Please contact the Committee at public@public-standards.gov.uk to express your interest. Please see the review's Terms of Reference here. Read the Committee's blog post'why CSPL are reviewing artificial intelligence in the public sector' here.

Safe Fleet, a global provider of safety solutions for fleet vehicles, announces the launch of its Intelligent Perimeter Safety Solutions that include its patents-pending Predictive Stop Arm and its Right-Hand Danger Zone protection system -- two innovative solutions that use predictive analytics, advanced sensors and radar technology to increase safety where students are most at risk, outside the bus. To date, the transportation industry has focused only on limited, reactive solutions that address recording oncoming driver behaviour, instead of proactive measures which directly reduce risk to students, helping them avoid accidents before they happen. Safe Fleet's proprietary Predictive Stop Arm uses radar technology to monitor oncoming vehicle traffic for probable stop arm violations and through the use of AI and predictive analytics, proactively notifies both the bus driver and students of potential danger through audible and visual warnings. If risk is detected, students are alerted not to cross the street. It displays visual warnings to alert the operator when risk is present, helping to reduce injury to students at the bus door and wheel well.

If you have any questions regarding the event please send an e-mail to katie.williams1@ibm.com To understand IBM's Code of Conduct for events click here. IBM may use tracking technology at this event. To learn more click here.

Reproducibility puts the science in the computer science of AI. It's how researchers can prove their AI systems are robust and reliable. To support reproducibility for AI models, Facebook today released PyTorch Hub in beta, an API and workflow for research reproducibility and support. PyTorch Hub can quickly publish pretrained models to a GitHub repository by adding a hubconf.py PyTorch Hub comes with support for models in Google Colab and PapersWithCode.

In 2018, researchers at MIT and the auto manufacturer BMW were testing ways in which humans and robots might work in close proximity to assemble car parts. In a replica of a factory floor setting, the team rigged up a robot on rails, designed to deliver parts between work stations. Meanwhile, human workers crossed its path every so often to work at nearby stations. The robot was programmed to stop momentarily if a person passed by. But the researchers noticed that the robot would often freeze in place, overly cautious, long before a person had crossed its path.

AI is the catalyst to business transformation all over the world. It decides on how you engage with your customers to how you operate as an organization. If you are wondering what you need to consider when planning your AI roadmap, then The AI Summit London Tech Week 2019, offers all the answers and more. Engage with world leading organisations, hear from the brightest minds and gleam exclusive insights into pioneering AI projects from all corners of industry, like never before. NetApp, with Data Fabric, is the data authority for AI.

IBM and the Massachusetts Institute of Technology (MIT) have joined forces to establish an MIT-IBM Watson AI Lab in Cambridge that will pursue research in artificial intelligence (AI) with a focus on healthcare and cybersecurity, as well as on commercialising AI technologies born out of the lab. Touted as one of the largest university-industry AI collaborations and investments, the 10-year, $240 million initiative is expected to hire and bring together over 100 AI-focused scientists, professors, and students. In addition to IBM's plan to commercialise technologies developed within the lab, the pair will encourage MIT faculty and students to launch new companies that will focus on commercialising inventions and technologies that are developed at the lab. "The field of artificial intelligence has experienced incredible growth and progress over the past decade. Yet, today's AI systems, as remarkable as they are, will require new innovations to tackle increasingly difficult real-world problems to improve our work and lives," said Dr John Kelly III, IBM senior vice president, Cognitive Solutions and Research.

Ford wants to use walking robots to help self-driving cars deliver packages. LAS VEGAS – The arrival of the machines is inevitable. And Sin City knows it. MGM Resorts International this year plans to install at Las Vegas resorts an unknown number of automated beverage systems programmed to mix hundreds of different drinks – all at the touch of a button. It's a job that for many years depended on the hands of living, breathing service workers.

Great Learning, India's leading Ed-tech platform for working professionals today announced that it is expanding its geographic footprint globally to Europe, Asia Pacific, Africa and the Middle East. The company will offer three of its most popular programs in Data Science & Business Analytics (PGP-DSBA - a special international variant of its business analytics program PGP-BABI ranked #1 in India for the last 4 years), Artificial Intelligence & Machine Learning (PGP-AIML) and Cyber Security (SACSP - Stanford Advanced Computer Security Program) in these geographies. Offered in association with two of the top universities of the world, Stanford University and The University of Texas, Austin, these online programs have already attracted learners from 17 countries including the UK, Singapore, South Africa, UAE, etc. These programs, designed and developed by the top-notch faculty of UT Austin and Stanford, are delivered online by Great Learning, utilizing its unique mentored-learning model where personalized mentorship is provided by expert instructors from Great Learning's 750 Global Guru network. The mentors include industry veterans from companies like Google, Microsoft, Amazon and Walmart.

I mentioned in my last article that Artificial Intelligence is a large field, to get to being a large field it must have been around for some time, which it has. The term Artificial Intelligence (AI) was coined in 1956 at the Dartmouth Conference (New Hampshire) by Stanford University Professor John McCarthy (although he was an assistant professor at Dartmouth at the time). You could argue that AI has deep roots in Formal Reasoning but that would open up a huge philosophical debate and would probably take significantly more space and time to write and read! So why now, if AI has been around for 70 years what has changed in the past few years that has propelled AI into the mainstream? The answer is that the perfect wave has hit, three things have come together to give us the adoption rates that we see.