The graph represents a network of 2,273 Twitter users whose tweets in the requested range contained "TopCyberNews", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 17 February 2020 at 18:20 UTC. The requested start date was Monday, 17 February 2020 at 01:01 UTC and the maximum number of tweets (going backward in time) was 5,000. The tweets in the network were tweeted over the 4-day, 1-hour, 45-minute period from Monday, 10 February 2020 at 23:14 UTC to Saturday, 15 February 2020 at 01:00 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.

Artificial intelligence (AI) experimentation is now prolific across South African companies, with many businesses demonstrating enthusiasm for AI. According to Business Tech (2019), over 45% of South African businesses say that they're already actively piloting AI within their organisations. Metaphorical robots are infiltrating organisations and reinventing business processes due to the rapid rise in Robotic Process Automation (RPA), which has become a readily available solution offered by ICT service providers. A year ago, says 4IR guru Arthur Goldstuck, "only 6% of South African enterprises were using robotics. Then came the RPA explosion. Now the figure stands at 37% (in Engineering News, 2019)."

DURBAN - The recent Covid-19 fuelled rush on retailers in South Africa, as consumers start stockpiling grocery staples, is leaving many shelves empty. Some, such as Makro, have recently announced that they will be "enforcing customer limits on shoppers … to give customers fair access to essential items." Morne Laubscher, CTO of Logicalis South Africa said, "Both online and brick-and-mortar retailers are experiencing a run on products, which is limiting their ability to service the needs of their entire customer base". Retailers have the data that they need for customer buying patterns but often aren't always able to access the benefits. The 2019 Global CIO Survey from Logicalis, a global provider of IT solutions which questioned 888 CIO's from around the globe, found that just under one in ten (9 percent) of respondents believe that their organisation is very successful at understanding the advantages of AI technology in some areas of business; whereas 44 percent believe their organisation is not very successful at all.

We consider sketched approximate matrix multiplication and ridge regression in the novel setting of localized sketching, where at any given point, only part of the data matrix is available. This corresponds to a block diagonal structure on the sketching matrix. We show that, under mild conditions, block diagonal sketching matrices require only O(stable rank / \epsilon^2) and $O( stat. dim. \epsilon)$ total sample complexity for matrix multiplication and ridge regression, respectively. This matches the state-of-the-art bounds that are obtained using global sketching matrices. The localized nature of sketching considered allows for different parts of the data matrix to be sketched independently and hence is more amenable to computation in distributed and streaming settings and results in a smaller memory and computational footprint.

We present a system that utilizes machine learning for tactic proof search in the Coq Proof Assistant. In a similar vein as the TacticToe project for HOL4, our system predicts appropriate tactics and finds proofs in the form of tactic scripts. To do this, it learns from previous tactic scripts and how they are applied to proof states. The performance of the system is evaluated on the Coq Standard Library. Currently, our predictor can identify the correct tactic to be applied to a proof state 23.4% of the time. Our proof searcher can fully automatically prove 39.3% of the lemmas. When combined with the CoqHammer system, the two systems together prove 56.7% of the library's lemmas.

The global artificial intelligence and education Market is significantly driven by the integration of intelligent algorithms as well as Advanced Technologies in to e-learning platforms. Education software, machine learning, and artificial intelligence are some of the Innovative learning models and Technologies change the rules and creating tremendous shift from the teaching methods. These technologies have completely transformed with a classroom. The sophistication level has increased tremendously with the increasing adoption of artificial intelligence and machine learning algorithms. These Technologies are becoming extremely useful for developing user-friendly decision support systems and used in knowledge acquisition applications, language translation, and information retrieval.

Conferences you speak at: Data Innovation Summit; Big Data Conference; EduData, etc.

With more than 2000 spoken languages, Africa's linguistic diversity is second only to Asia. A third of the world's languages is spoken by the 1.2 billion people living within her 54 countries. But the language of artificial intelligence is yet to gain fluency. It has become hackneyed to weave AI into every conversation about technology and society. AI will take away jobs.

Recurrent neural networks are extremely appealing for sequence-to-sequence learning tasks. Despite their great success, they typically suffer from a shortcoming: they are prone to generate unbalanced targets with good prefixes but bad suffixes, and thus performance suffers when dealing with long sequences. We propose a simple yet effective approach to overcome this shortcoming. Our approach relies on the agreement between a pair of target-directional RNNs, which generates more balanced targets. In addition, we develop two efficient approximate search methods for agreement that are empirically shown to be almost optimal in terms of either sequence level or non-sequence level metrics. Extensive experiments were performed on three standard sequence-to-sequence transduction tasks: machine transliteration, grapheme-to-phoneme transformation and machine translation. The results show that the proposed approach achieves consistent and substantial improvements, compared to many state-of-the-art systems.

CAPE TOWN 17th March – AI Expo Africa is the continent's largest B2B trade-focused artificial intelligence (AI) business event. The expo, which is now in its third year, will be held at Century City Convention Centre in Cape Town on 3rd and 4th September 2020. Zindi, Learning Machines – which provides a number of services across machine learning and data science – and FinChatBot, which develops AI-powered chat bots for the financial services industry, will showcase their solutions at AI Expo Africa's Innovation Cafe. Other companies that will exhibit at AI Expo Africa's Innovation Cafe include data science specialists Ashanti AI and visitor management solutions provider WizzPass. AI Expo Africa Event Co-founder Dr Nick Bradshaw stated, "It's great to welcome back supporters like City of Cape Town, FinChatBot and Zindi, the latter launched at our 2018 event and have gone onto be a massive success. It's also great to introduce brand new supporters and companies like Learning Machines, WizzPass and Ashanti AI. Our goal is to promote the newest and best AI, RPA and Data Science companies and startups via our various media platforms to maximise brand exposure and generate new business for the growing 4IR community of suppliers that is emerging in Africa."