IBM has created an AI development program called Project Debater which is capable of ‘arguing effectively within the context of a formal debate’. In 2019 it participated in a debate about whether preschool should be subsidized against world renowned debater Harish Natarajan. Each participant was given 15mins prep time and a 4min presentation window. Although Harish was judged to have won the debate, Project Debater had been able to form various logical statements and arguments over the course of the debate. Debating is a very subjective area and Project Debater performed exceptionally well for a computer. Read more at https://www.extremetech.com/extreme/320999-ibm-built-an-ai-capable-of-holding-its-own-against-humans-i

More businesses are turning to AI for cyber security solutions. AI can detect and analyse real-time network activities faster with better accuracy than traditional cyber security methods. Despite its apparent benefits, using AI poses unique risks due to the technology’s higher complexity and the amount of data required to remain updated against modern attacks. The enterprise can also be susceptible to adversarial AI attacks. Human insights are still needed to deal with these vulnerabilities in AI and machine learning security solutions.Read more at: https://www.thesslstore.com/blog/artificial-intelligence-in-cyber-security-the-savior-or-enemy-of-your-business/

Protecting and preserving personally identifiable information (PII), intellectual property, intelligence insights, and other forms of sensitive information has never been more criticalFully Homomorphic Encryption (FHE) is an approach to data security that delivers mathematical proof of encryption by using cryptographic means, providing a new level of certainty around how data is stored and manipulated.DARPA continues to lead R&D investment with the latest project seeing collaboration between Intel, Galois and two others part of the project team.https://www.darpa.mil/news-events/2021-03-08image credit: Pete Linforth from Pixabay 

Typically research papers are peer reviewed before publication (particularly in top journals). While research fraud is not new, the co-director of a prestigious artificial intelligence lab in Cambridge, Massachusetts USA found his name on papers he didn't co-author. What if Algorithims (AI) could scan existing research papers and generate new content? Would you be able to distinguish? Would authors be aware?https://www.wired.com/story/ai-research-paper-real-coauthor-notimage credit: Image by Anja from Pixabay 

AI and machine learning are becoming an essential component of cyber security. AI's advantage's lie in its ability to replicate the human skillset at much larger and efficient scale by analyzing mass amounts of data and learning from them in a smaller time-frame. This allows for quicker identification and detection of threats and learning of these threats to mitigate potential risks in the future. Read more at: https://becominghuman.ai/why-you-should-use-artificial-intelligence-in-cybersecurity-204dbe33326c

Poaching is one of the leading factors for dwindling population of protected species. PAWS (Protection Assistant for Wildlife Security) is an AI system that tracks and predicts poaching activities in a given area. It uses previous data from SMART (Spatial Monitoring and Reporting Tool) to calculate the most efficient patrol routes for rangers. As more poaching data is added to SMART, PAWS gets better at predicting where poachers are likely going to hunt next. PAWS uses computational game theory and AI simulation to understand possible future poaching strategies for mitigating attacks with limited resources. Read more at: https://www.engadget.com/paws-anti-poaching-ai-predicts-where-illegal-hunters-will-show-up-next-20361