Samsung Electronics will introduce its new products and solutions to its business partners around the world at Samsung Forum 2019. During the two-month event, strategic products including the 2019 QLED TV lineup as well as customized products for regional markets will be showcased. Based on'New Bixby,' Samsung's intelligence platform, Connected Solution will also be exhibited where global business partners can interact with various Samsung products. Starting with the European Forum, Samsung will invite media and partners from Europe, Southwest Asia and Latin America to Porto of Portugal from February 12th to 22nd. From March 7th to 11th, Samsung will host the Middle East and CIS (Commonwealth of Independent States) Forum in Antalya of Turkey.

The graph represents a network of 3,408 Twitter users whose tweets in the requested range contained "futureofwork ", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Tuesday, 19 February 2019 at 14:05 UTC. The requested start date was Tuesday, 19 February 2019 at 01:01 UTC and the maximum number of days (going backward) was 14. The maximum number of tweets collected was 5,000. The tweets in the network were tweeted over the 1-day, 11-hour, 23-minute period from Sunday, 17 February 2019 at 13:37 UTC to Tuesday, 19 February 2019 at 01:00 UTC.

Machine Learning as a Service Market to reach USD 16.13 billion by 2025 Machine Learning as a Service Market valued approximately USD 0.87 billion in 2017 is anticipated to grow with a healthy growth rate of more than 43.9% over the forecast period 2018-2025. Machine learning as a service is a significant range of solutions and services that are offered by cloud service providers. The tools offered by service providers include APIs, data visualization, natural language processing, face recognition, deep learning, and predictive analytics. The main benefit associated with these services is that the customers are able to quickly start with machine learning with no need to install or download any software on their servers. Enhancements in technology, growth in data volume and rise in IT spending in some of the developing regions are the major factors which are driving the growth in the global market.

The members of the Global University Leaders Forum community convened at the World Economic Forum Annual Meeting 2019 to discuss their role in our ever-changing world. Here are six topics that were top of the agenda as the members considered the future of the university and its role in society. Today data is omnipresent and often overwhelming. By way of example, Domo's Data Never Sleeps 6.0 reported that in 2018 Google conducted an average 3.8 million searches per minute. Though not all graduates will enter data-related fields, universities are starting to work towards increasing data literacy in their student body by adding data science courses and challenges for social science majors so that graduates can effectively communicate with their data-oriented peers and co-workers.

In 1950, Norbert Wiener's The Human Use of Human Beings was at the cutting edge of vision and speculation in proclaiming: But this was his book's denouement, and it has left us hanging now for 68 years, lacking not only prescriptions and proscriptions but even a well-articulated "problem statement." We have since seen similar warnings about the threat of our machines, even in the form of outreach to the masses, via films like Colossus: The Forbin Project (1970), The Terminator (1984), The Matrix (1999), and Ex Machina (2015). But now the time is ripe for a major update with fresh, new perspectives -- notably focused on generalizations of our "human" rights and our existential needs. Concern has tended to focus on "us versus them" (robots) or "gray goo" (nanotech) or "monocultures of clones" (bio). To extrapolate current trends: What if we could make or grow almost anything and engineer any level of safety and efficacy desired?

In the past decade, sparse principal component analysis has emerged as an archetypal problem for illustrating statistical-computational tradeoffs. This trend has largely been driven by a line of research aiming to characterize the average-case complexity of sparse PCA through reductions from the planted clique (PC) conjecture - which conjectures that there is no polynomial-time algorithm to detect a planted clique of size $K = o(N^{1/2})$ in $\mathcal{G}(N, \frac{1}{2})$. All previous reductions to sparse PCA either fail to show tight computational lower bounds matching existing algorithms or show lower bounds for formulations of sparse PCA other than its canonical generative model, the spiked covariance model. Also, these lower bounds all quickly degrade with the exponent in the PC conjecture. Specifically, when only given the PC conjecture up to $K = o(N^\alpha)$ where $\alpha < 1/2$, there is no sparsity level $k$ at which these lower bounds remain tight. If $\alpha \le 1/3$ these reductions fail to even show the existence of a statistical-computational tradeoff at any sparsity $k$. We give a reduction from PC that yields the first full characterization of the computational barrier in the spiked covariance model, providing tight lower bounds at all sparsities $k$. We also show the surprising result that weaker forms of the PC conjecture up to clique size $K = o(N^\alpha)$ for any given $\alpha \in (0, 1/2]$ imply tight computational lower bounds for sparse PCA at sparsities $k = o(n^{\alpha/3})$. This shows that even a mild improvement in the signal strength needed by the best known polynomial-time sparse PCA algorithms would imply that the hardness threshold for PC is subpolynomial. This is the first instance of a suboptimal hardness assumption implying optimal lower bounds for another problem in unsupervised learning.

Yet the healthcare industry has been slow to commit to its potential. As recently as 2016, a Forrester Consulting survey found that just 34% of healthcare organizations had adopted predictive analytics, compared with 51% in all other industries. Healthcare was similarly behind in cognitive computing, at 23% versus 40% elsewhere. Among the pioneers, some organizations are already using AI to reduce physical trips to the doctor's office, improve patient care and rethink care delivery models that date to the 19th century. "I believe we can get to a world where we aren't just identifying your likelihood of utilizing the emergency room or being hospitalized, but getting in front of those situations and delivering proactive care," says Dr. Arta Bakshandeh, senior medical officer at Alignment Healthcare.

Summary: Artificial Intelligence in Healthcare Market Overview: Artificial intelligence (AI) can be defined as the science and engineering adopted to design intelligent machines, especially intelligent computer programs. AI is an intelligent system that applies various human intelligence based functions such as reasoning, learning, and problem-solving skills on different disciplines such as biology, computer science, mathematics, linguistics, psychology, and engineering. AI is widely applicable in medication management, treatment plans, and drug discovery. The global AI in healthcare market was valued at $1,441 million in 2016, and is estimated to reach at $22,790 million by 2023, registering a CAGR of 48.7% from 2017 to 2023. The growth of the global AI in healthcare market is driven by the ability of AI to improve patient outcomes, need to increase coordination between healthcare workforce & patients, increase in adoption of precision medicine, and a notable rise in venture capital investments.

UAE-based automotive company W Motors' has announced the unveiling of MUSE at Auto Shanghai 2019 on April 16. The fully-electric MUSE features a Level 4 / Level 5 autonomous driving system, innovative user interfaces and cloud-computed connectivity, as well as several interior configurations catering to different business needs and consumer requirements. It will be fully produced in Dubai, UAE by W Motors at the all-new production facility of which the first phase is set to be completed in the last quarter of 2019. Pioneers of the future of driving, W Motors is the first and only automotive developer in the Middle East - in partnership with sister company ICONIQ Motors - to release a self-driving vehicle, designed to be on the road for EXPO 2020 in Dubai. MUSE was developed by W Motors and ICONIQ Motors in collaboration with international partners AKKA Technologies, Magna Steyr and Microsoft USA, each offering highly specialized and cutting-edge technologies in the realm of advanced autonomous driving solutions.

The world is inundated with data. Take just the global financial markets. They generate vast amounts of data – share prices, commodity prices, indices, option and futures prices, to name just a few. But data is of no use if there aren't people able to collect, collate, analyse and apply it to the benefit of society. All that data generated by global financial markets gets used for asset and wealth management – and it must be properly analysed and understood to inform good decision making.