BELGRADE – When hundreds of video cameras with the power to identify and track individuals started appearing in the streets of Belgrade as part of a major surveillance project, some protesters began having second thoughts about joining anti-government demonstrations in the Serbian capital. Local authorities assert the system, created by Chinese telecommunications company Huawei, helps reduce crime in the city of 2 million. Critics contend it erodes personal freedoms, makes political opponents vulnerable to retribution and even exposes the country's citizens to snooping by the Chinese government. The cameras, equipped with facial recognition technology, are being rolled out across hundreds of cities around the world, particularly in poorer countries with weak track records on human rights where Beijing has increased its influence through big business deals. With the United States claiming that Chinese state authorities can get backdoor access to Huawei data, the aggressive rollout is raising concerns about the privacy of millions of people in countries with little power to stand up to China.

In the financial services industry, the application of machine learning (ML) methods has the potential to improve outcomes for both businesses and consumers. In recent years, improved software and hardware as well as increasing volumes of data have accelerated the pace of ML development. The UK financial sector is beginning to take advantage of this. The promise of ML is to make financial services and markets more efficient, accessible and tailored to consumer needs. At the same time, existing risks may be amplified if governance and controls do not keep pace with technological developments.

We will discuss a little about what it means to develop AI in a transparent way. We will introduce our interpretability toolkit which enables you to use different state-of-the-art interpretability methods to explain your models decisions. By using this toolkit during the training phase of the AI development cycle, you can use interpretability output of a model to verify hypotheses and build trust with stakeholders. You can also use the insights for debugging, validating model behavior, and to check for bias. You can also use this toolkit at inferencing time to explain the predictions of a deployed model to the end users.

After becoming the first nation to appoint a minister for artificial intelligence (AI) in 2017, the United Arab Emirates on Wednesday launched what it calls the'world's first AI university' in Abu Dhabi, with the opening of the Mohammad Bin Zayed University of Artifical Intelligence (MBZUAI). MBZUAI will be the world's first graduate university with a dedicated focus on AI. According to the university's website, MBZUAI is "a graduate-level, research-based academic institution that offers specialized degree programs for local and international students in the field of Artificial Intelligence." Located in Masdar City, Abu Dhabi, the university has begun accepting applications for masters and PhD programmes, with classes scheduled to begin in September 2020. Abu Dhabi's crown prince, Shaikh Mohammad Bin Zayed Al Nahyan, tweeted on the occasion, "Launching of the world's first graduate-level artificial intelligence university in Abu Dhabi echoes the UAE's pioneering spirit, and paves the way towards a new era of innovation and technological advancement that benefits the UAE and a world."

Contrary to common fears around how robots will impact jobs, leaders across the globe are reporting increased adoption of artificial intelligence (AI) and robots at work and many are welcoming it with love and optimism. According to the second annual "AI at Work" study of 8,370 employees, managers and HR leaders across 10 countries, including the UAE, conducted by Oracle and research firm Future Workplace, 64% of the people trust a robot more than their managers and half have turned to a robot instead of their manager for advice. Rahul Misra, vice-president for applications at Oracle Lower Gulf, told TechRadar Middle East that 82% of people think robots can do things better than their managers. In the UAE, respondents said robots are better at maintaining work schedules (42%), problem-solving (34%) and providing unbiased information (32%) while the top three tasks where managers are better than robots were understanding feelings (46%), coaching them (32%) and evaluating team performance (25%). "UAE is building a future based on tech innovation. Anything where the managers' role does not have an emotional quotient, people believe they can work with a fact-based model," he said.

IBM has joined efforts to build a fully autonomous ship capable of journeying across the Atlantic. The tech giant announced on Wednesday that it will participate in a global consortium designed to help materialize the ship, called the Mayflower, which will make the same voyage as its namesake that originally carried pilgrims to what's now the continental US. Once completed, the self-navigating craft is slated to make a 3,000-mile journey across the Atlantic on September 2020 - a date that coincides with a 400-year anniversary for the original Mayflower's voyage. Using artificial intelligence designed by IBM, the Mayflower is being built to adeptly avoid ocean obstacles and complete it's journey from Plymouth England to Plymouth Massachusetts free of any human intervention. IBM and partner Promare, a marine research organization, are positioning the ship as a way of advancing research via reducing barriers like cost and human resources.

Introhive is seeking an ambitious, well-rounded senior Data Scientist to join our growing Data Science department. This position would be based in our Fredericton office. Introhive offers a unique opportunity to work on very large data sets and solve challenging business problems using ML, Deep Learning and NLP. If this sounds intriguing, then we would like to talk to you about this key role in within the technical team.

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.

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.

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.