Roughly speaking, my machine learning journey began on Kaggle. "Regression models predict continuous-valued real numbers; classification models predict'red,' 'green,' 'blue.' Typically, the former employs the mean squared error or mean absolute error; the latter, the cross-entropy loss. Stochastic gradient descent updates the model's parameters to drive these losses down." Furthermore, to fit these models, just import sklearn. A dexterity with the above is often sufficient for -- at least from a technical stance -- both employment and impact as a data scientist. In industry, commonplace prediction and inference problems -- binary churn, credit scoring, product recommendation and A/B testing, for example -- are easily matched with an off-the-shelf algorithm plus proficient data scientist for a measurable boost to the company's bottom line. In a vacuum I think this is fine: the winning driver does not need to know how to build the car.

At Computex this year, chipmakers are looking to bring their processors up to date with support for modern technologies - machine learning, artificial intelligence, augmented reality and virtual reality. ARM, the British semiconductor company (now owned by Softbank) creates reference ARM designs that other OEM's follow. The company will announce its latest ARM Cortex-A75 processor design, which the company claims will provide 22 per cent improvement in performance over the previous Cortex-A73 design. Alongside the A75 design, ARM will also be unveiling the Cortex-A55 design which is expected to provide the highest power efficiency in mid-range processors. In addition, the company will also unveil the Mali-G72 graphics processor which will be a 25 per cent improvement over the erstwhile Mali-G71.

On the eve of Computex, Taiwan's big showpiece event where PC makers roll out the latest and best implementations of Intel CPUs, mobile rival ARM is announcing its own big news with the unveiling of a new generation of ARM CPUs and GPUs. Official today, the ARM Cortex-A75 is the new flagship-tier mobile processor design, with a claimed 22 percent improvement in performance over the incumbent A73. It's joined by the new Cortex-A55, which has the highest power efficiency of any mid-range CPU ARM's ever designed, and the Mali-G72 graphics processor, which also comes with a 25 percent improvement in efficiency relative to its predecessor G71. The efficiency improvements are evolutionary and predictable, but the revolutionary aspects of this new lineup relate to artificial intelligence: this is the first set of processing components designed specifically to tackle the challenges of onboard AI and machine learning. Plus, last year's updates to improve performance in the power-hugry tasks of augmented and virtual reality are being extended and elaborated.

IN JULY 2011 Sebastian Thrun, who among other things is a professor at Stanford, posted a short video on YouTube, announcing that he and a colleague, Peter Norvig, were making their "Introduction to Artificial Intelligence" course available free online. By the time the course began in October, 160,000 people in 190 countries had signed up for it. At the same time Andrew Ng, also a Stanford professor, made one of his courses, on machine learning, available free online, for which 100,000 people enrolled. Both courses ran for ten weeks. Such online courses, with short video lectures, discussion boards for students and systems to grade their coursework automatically, became known as Massive Open Online Courses (MOOCs).

ARM has unveiled a set of new processors to provide the brainpower for our mobile devices to cope with advanced artificial intelligence (AI), virtual reality (VR), and mixed reality (MR) technologies. On Monday, the British semiconductor giant said the new Cortex-A75 and Cortex-A55 processors, alongside the new Mali-G72 graphics processor, have been designed to "address the changing nature of computers driven by AI and other more human-like experiences." "Distributed intelligence" is at the heart of this trend, which includes connecting AI and the cloud, on-device learning, enhanced security and privacy, and the use of 4K, HDR, and 5G for more "human-like" interfaces. ARM says that by providing low-power, efficient and powerful processors, device vendors will be able to explore the possibilities of distributed intelligence, and the new Cortex-A architecture enables system-on-a-chip (SoC) architecture designers to scale up to eight cores in a single cluster. The Cortex-A75 and Cortex-A55 have been designed with this concept in mind.

We are aware of the devastating effect HIV can have on the immune system, but a new studysuggests the virus may also adversely affect brain development. In groundbreaking research, scientists have found young HIV positive patients with limited or no treatment for their condition had significant disruptions in brain structure, poorer strength and efficiency of connections, and lessened cognitive performance, when compared to their peers without the virus. A new study published online in Brain Connectivity found that limited-treated or untreated HIV infections in young adults may affect their brain connections, which in turn compromises their cognitive abilities. The study found that, in addition to having visible structural and connectivity differences from uninfected peers, HIV positive young adults performed worse on cognitive tests involving tasks such as learning and recalling information. "The most interesting aspect of this study was that it was performed in young adults with limited or no history of HIV treatment."

In a recent post about Deep Learning applications, platforms, limitations and quantum computing we have announced a panel discussion on "How Artificial Intelligence is disrupting Industries" which took place on 25 May 2017 in Cape Town. This event was hosted by Far Ventures, a start-up studio and incubator that aims to foster technology entrepreneurship in Africa by founding and growing start-ups that can positively impact people's lives through technology. It was also supported by the Machine Intelligence Institute of Africa (MIIA), an innovative community and accelerator for Machine Intelligence and Data Science Research and Applications to help transform Africa. This post includes the links to the introductory presentation as well as the video of the panel discussion. Photos of the MIIA event can be found here. Photos of the MIIA event can be found here.

In the wake of the recent Manchester terrorist attacks, in which 22 people--mostly parents, teenagers, and children as young as eight years old--were murdered by a suicide bomber, the question that lingered on so many people's minds is, "how?" How could he, the bomber, do it? It's a question that many people have found themselves asking too often, not just after highly publicized attacks in the U.S., but also in countries like Kenya and Nigeria where terror attacks by militant groups such as Boko Haram and al-Shabaab attract less global attention but are no less deadly, or heart-wrenchingly awful. And yet, despite behaviors that many would label immoral, terrorists often couch their activities in moral terms--invoking concepts such as "social cleansing" and "moral purification," attacking people and symbols that they believe are representative of moral failings. But how can people allegedly motivated by morality engage in behaviors that, from the outside, appear to be so clearly immoral? Agustín Ibáñez, a cognitive science researcher at Argentina's Ineco Foundation at Favaloro University, and Adolfo Garcia, a researcher at the National Scientific and Technical Research Council (CONICET), took an interesting tact towards understanding how the mind of a terrorist differs from the mind of, well, people who don't commit acts of terror.

A herd of elephants walks in front of Mount Kilimanjaro in Amboseli National Park. A centuries-old problem that has affected nearly every region on Earth is about to get a high-tech solution. Artificial intelligence company Neurala is using machine learning coupled with cameras and drones to put a stop to the poaching crisis in Africa. Focusing on the rhino population (which, for just black rhinos, has dwindled by 97.6 percent since 1960) and African elephants (35,000 of which were killed last year), the company is enhancing the Lindbergh Foundation's effort to track and predict the paths of both at-risk animals and the poachers who are hunting them. "We believe that Neurala is the first to have AI software that can identify wildlife and poachers," Neurala CEO Massimiliano Versace told the Observer.

The Middle East and North Africa's youthful, fast-urbanizing population are perfectly placed to embrace technology and reap the rewards of the Fourth Industrial Revolution. Much has been written already about the arrival of the Fourth Industrial Revolution (4IR) and the opportunity that the convergence of its new technologies offers in terms of building value into production systems and economies around the world. In one sense, the playing field could be levelled out. Localized production is being made more feasible for many small producers, setting developing communities on a path towards self-sufficiency, while falling costs could enable factories of all sizes to boost their productivity levels. However, on the opposite side of the equation, news headlines have been dominated by predictions that human workers will be substituted by robots, leading to widespread job losses and heightened societal challenges. Additionally, doubt has been shed on the ability of regions that are less industrialized, or those with fractured economies and infrastructure, to be able to respond to these disruptions and compete effectively in the future.