D2L, a global learning technology company, shared the launch of a new, free Introduction to AI Ethics and Governance course, built in partnership with AI specialists, INQ Consulting. With the surge of AI across industries and its potential to streamline business activities, organizations are looking to incorporate AI technologies into their operations. Through this course, individuals can learn about AI ethics, governance and the emergence of AI regulation. Moreover, learners can also expect to receive some practical advice for safely deploying AI governance systems to best maximize AI’s benefits and mitigate its possible risks. Combining INQ Consulting’s expertise surrounding AI law and D2L’s cutting-edge course-building technology, the crafting of this learning experience marks the first time that the two companies have worked together. The course can now be found on D2L Open Courses, an online course platform that offers courses to the general public.
CBA’s system uses a combination of machine learning, natural language processing and large language models on public data, text analysis and graph concepts to identify abusive relationships. Graph concepts, or graph theory, refers to combining different graphs and data sources with math to develop predictive models — which, in this case, can match certain words and phrases to a pattern of behavior. Large language models are capable of producing original content, and power emerging technology such as generative artificial intelligence programs. Financial crooks are using large language models to improve phishing attacks and malware. Banks such as JPMorgan Chase are using the technology to fight email fraud and other attacks embedded in financial communication. CBA’s use is similar to Chase. The Australian bank is analyzing evidence of sustained abuse across criteria in payments, such as the value of the transaction, the frequency and velocity of transactions and the types of messages. CBA built its model in partnership with AI firm H20.ai. It is available on GitHub, a large global platform that hosts source code.
For true responsible governance of AI, we therefore need to avoid a single point of failure. we need strong independent and democratic oversight, involving not only a national regulator but also civil society, independent academics and the international community. The governance structure must be multi-stakeholder and multilateral. One objective is to minimise conflicts of interest with commercial goals and focus on safety-first R&D. Another is to protect against the possibility that a lab’s system falls into the wrong hands or becomes a dangerous runaway entity. Having labs share their results means the other institutions would be there to defend society. While a lot of uncertainty remains, wrestling with these questions is urgent. Reports suggest that OpenAI may have recently made a breakthrough, Q*, which may have greatly increased reasoning and mathematical abilities. If and when this is proven to be true, we could have become closer to AGI.
In their study, the U.C. Berkeley scientists explore a hybrid approach that leverages the strengths of reinforcement learning and interactive imitation learning. Their method, RLIF, is predicated on a simple insight: it’s generally easier to recognize errors than to execute flawless corrections. This concept is particularly relevant in complex tasks like autonomous driving, where a safety driver’s intervention—such as slamming on the brakes to prevent a collision—signals a deviation from desired behavior, but doesn’t necessarily model the optimal response. The RL agent should not learn to imitate the sudden braking action but learn to avoid the situation that caused the driver to brake. “The decision to intervene during an interactive imitation episode itself can provide a reward signal for reinforcement learning, allowing us to instantiate RL methods that operate under similar but potentially weaker assumptions as interactive imitation methods, learning from human interventions but not assuming that such interventions are optimal,” the researchers explain.
Artificial intelligence monitoring startup ArthurAI Inc. is looking to make its presence felt in the generative AI industry with the launch of its first chatbot builder, Arthur Chat. The service has the ability to integrate with almost any large language model, making it extremely adaptable, the company said. In addition, it also provides strong protections via its integration with Arthur Shield, a tool that prevents proprietary data from being leaked outside of its customer’s servers, and safeguards against inappropriate content generation. Finally, it comes with built-in protection against so-called “hallucinations,” ensuring that chatbots won’t go astray and start making up answers on the spot. When customers get started with Arthur Chat, they’ll be able to choose their preferred LLM as the foundation of their new chatbot. Then, they can use its RAG capabilities to link the chatbot to their internal datasets and knowledge bases to ensure it is always fed with the most up-to-date information it needs. Their chatbots will be more flexible with Arthur Chat too, as it enables customers to switch quickly between different LLMs, based on the complexity or type of questions asked by users.
Simplr, a provider of AI-powered solutions for enterprise CX dive into the ways in which generative AI is transforming customer service and experience for enterprises. AI’s impact on customer service is twofold: It dramatically improves the quality of customer service interactions, and it significantly increases the types of customer interactions which can be handled via automation. Improved customer service interactions via AI–in the form of resolving customer issues quicker and with more accuracy–results in greater customer loyalty, longer-term, mutually beneficial customer relationships, and more cross sell and upsell opportunities. Increased automation via AI significantly drives down overall customer service costs. Both those trends will catch the eye of the CEO and CFO at large companies, and it will result in renewed interest from the top down in the power of great customer service, to attract and retain customers. In turn, business leaders will allocate much larger investments in CX as a whole, opening up opportunities for customer service leaders to experiment and drive further innovation.
Moody’s Corporation has announced the launch of Moody’s Research Assistant, a first-of-its-kind search and analytical tool powered by generative artificial intelligence (GenAI). As the first GenAI-powered research tool commercially available for financial market participants, Moody’s Research Assistant synthesizes vast amounts of information so users can assess lending or investment opportunities, monitor developments, compare entities, and enhance analytical workflows rapidly and at scale. Grounded in Moody’s extensive proprietary content in combination with the latest GenAI technology, Moody’s Research Assistant allows users to generate more holistic risk insights faster. Moody’s Research Assistant covers the latest rating actions, credit opinions, and research reports from Moody’s Investors Service to provide real-time answers for users. Ultimately, Moody’s Research Assistant will expand to leverage more of Moody’s data and content across risk domains including credit, climate, cyber, compliance, supply chain, and more.
Big Tech is becoming increasingly assertive in its maneuverings to protect its hold over the market. Make no mistake: though OpenAI was in the crosshairs this time, now that we’ve all seen what it looks like for a small entity when a big firm it depends on decides to flex, others will be paying attention and falling in line. Regulation could help, but government policy often winds up entrenching, rather than mitigating, the power of these companies as they leverage their access to money and their political clout. Take Microsoft’s recent moves in the UK as an example: last week it announced a £2.5 billion investment in building out cloud infrastructure in the UK, a move lauded by a prime minister who has clearly signaled his ambitions to build a homegrown AI sector in the UK as his primary legacy.
Logik.io’s Cosmo AI suite launches with its first game-changing capability, Cosmo FunctionAssist. Cosmo FunctionAssist is an intelligent rule-writing assistant built to make configuration administration simpler than ever by using generative AI to create advanced rules. Within Logik.io, admins can write the rule they want to create in plain English, and Cosmo FunctionAssist will instantly return a perfectly optimized set of rules. Cosmo FunctionAssist makes rule creation, a traditionally complicated task in other solutions, fast and simple. Logik.io’s forthcoming AI capabilities include: Smart Predictions & Auto-Suggestions, which will save end-users time quoting by auto-suggesting options based on previous selections. Rule Optimization Suggestions, which will make process improvements faster, simpler, and more automated via intelligent suggestions. Inline Admin Help & Support, which will enable CPQ and Commerce admins to be more effective and efficient by providing them with real-time, in-context answers and training on any questions they have as they work.
Janover Inc., an AI-enabled platform for commercial real estate transactions, announced that its now offering its AI chatbot interface under a software-as-a-service (“SaaS”) model to a select number of commercial lenders. The first collaboration is with Gelt Financial, a leading and innovating commercial real estate lender providing debt to real estate owners across the U.S. Janover has named its AI, Burrito, as each conversation “ought to be unique and delicious”. Multifamily, commercial real estate, and Small Business Administration (“SBA”) lenders can now dramatically enhance engagement on their website, quickly qualify and disqualify borrowers, and provide a more delightful experience for website users. Janover’s AI chatbot interacts 24/7 with users in real-time to resolve issues, coordinate transactions, and answer questions, in addition to handling lead generation and qualification.