An introduction to the OpenCog Hyperon framework for Artificiai General Intelligence is presented. Hyperon is a new, mostly from-the-ground-up rewrite/redesign of the OpenCog AGI framework, based on similar conceptual and cognitive principles to the previous OpenCog version, but incorporating a variety of new ideas at the mathematical, software architecture and AI-algorithm level. This review lightly summarizes: 1) some of the history behind OpenCog and Hyperon, 2) the core structures and processes underlying Hyperon as a software system, 3) the integration of this software system with the SingularityNET ecosystem's decentralized infrastructure, 4) the cognitive model(s) being experimentally pursued within Hyperon on the hopeful path to advanced AGI, 5) the prospects seen for advanced aspects like reflective self-modification and self-improvement of the codebase, 6) the tentative development roadmap and various challenges expected to be faced, 7) the thinking of the Hyperon team regarding how to guide this sort of work in a beneficial direction ... and gives links and references for readers who wish to delve further into any of these aspects.

From Deep Blue's victory over chess grandmaster Garry Kasparov to AlphaGo being the first computer program to defeat a Go World Champion, unbeatable superhuman agents have paved a new path for remarkable advancements made in AI. However, the primary question remains whether AI can create agents that can use language to negotiate and collaborate with others to achieve strategic goals in a manner comparable to humans. As it involves players mastering the art of understanding other people's perspectives and devising methods appropriately to persuade them to make agreements and form alliances with others, Diplomacy has long been considered a near-impossible challenge in AI. The complexity of human emotions makes it simple to learn these diplomatic skills. Nevertheless, the question remains: can artificially intelligent machines achieve this level of understanding and persuasion skills?

While artificial intelligence long ago surpassed human capability in Chess, and more recently Go -- and let us not forget Doom -- other more complex board games still present a challenge to computer systems. Until very recently, Stratego and Diplomacy were two of those games, but now AI has become table-flipping good at the former and passably human at the latter. On the surface, you might think that it's just because these games require a certain level of long-term planning and strategy. But so do Go and Chess, just in a different way. The crucial difference is actually that Stratego and Diplomacy are games of strategy based on imperfect information.

Facebook, or as we're supposed to call them now Meta, announced earlier today that their CICERO artificial intelligence has achieved "human-level performance" in the board game Diplomacy, which is notable for the fact that's a game built on human interaction, not moves and manoeuvres (like, say, chess). If you've never played Diplomacy, and so are maybe wondering what the big deal is, it's a board game first released in the 1950s that is played mostly by people just sitting around a table (or breaking off into rooms) and negotiating stuff. There are no dice or cards affecting play; everything is determined by humans communicating with other humans. So for an AI's creators to say that it is playing at a "human level" in a game like this is a pretty bold claim! One that Meta backs up by saying that CICERO is actually operating on two different levels, one crunching the progress and status of the game, the other trying to communicate with human levels in a way we would understand and interact with.

While AI may appear to benefit the good guys in security at the moment, the pendulum may swing when the bad guys fully embrace it and use it to do things like unleash malware infections that can learn from their hosts. One aspect of imperial participation in the center concerns the transparency of decision making in intelligent machines. Indeed, Kuhner et al. suggest "that algorithmic processes should play a role in a more just society, suggesting that in the future, it may be possible to use the algorithmic process to demonstrate the legality, fairness and transparency of a human decision. With new data protection laws going into effect next year and the pace of machine learning accelerating, it's time for marketers to catch up with AI. Watchdogs like AI now appear to expose and root out prejudice.

How many of you had a decent conversation with a chatbot? Today we are going to look at the paper "Why AI is harder than you think" published by Melanie Mitchell of Santa Fe Institute. Let's define two words used in the paper: This paper argues that the cycles of AI spring and AI winter come about by people making too overconfident predictions and then everything breaks down. Mitchell has provided examples of times where people make overconfident predictions and outlined four fallacies that researchers make. I found this paper interesting and sharing it here with you.

Most of today's chatbots are highly specific in their conversations (according to their domain of usage) and users can't afford to drift away from their expected use. They are not good with retaining context from past conversations, sometimes give meaningless, illogical responses and quite easily give the response, "I don't know". Open-domain chatbots are conversational agents that can chat about anything and have basic knowledge about the real world. In the research paper "Towards a Human-like Open-Domain Chatbot", Google introduced Meena. Meena is claimed to be the smartest chatbot, highly sensible and specific in its responses, unlike other chatbots.

The world watched in wonder in February as NASA's robotic rover Perseverance successfully landed on the surface of Mars with the goal of searching for evidence of past life on the red planet. The technology itself was, of course, astounding. But what really captivated the public was the video taken by a couple of miniature cameras from consumer-grade smartphones that were attached to the landing module. The idea came from NASA deputy program manager Matt Wallace, who was inspired when his daughter showed him a video she made by attaching a camera to her body during gymnastics. "I felt for a moment I had a glimpse into what it would be like if I could do a back flip," he told The New York Times.

The UK Robotics Growth Partnership (RGP) aims to set the conditions for success to empower the UK to be a global leader in Robotics and Autonomous Systems whilst delivering a smarter, safer, more prosperous, sustainable and competitive UK. The aim is for smart machines to become ubiquitous, woven into the fabric of society, in every sector, every workplace, and at home. If done right, this could lead to increased productivity, and improved quality of life. It could enable us to meet Net Zero targets, and support workers as their roles transition from menial tasks. One thing that's striking is that although robotics holds so much potential, they are not yet ready.

Businesses that focus only on customer experience may be missing a significant opportunity to connect with people on a deeper level. We don't pour that delightful first cup of life-giving coffee and think, "I am the end user of this coffee." So why does the business world insist on grouping--and trying to understand--people as customers when, before anything else, we are human? We are messy, inconsistent, and, perhaps most of all, emotional--and it's time for businesses to acknowledge, respect, and account for this. The fields of philosophy, religion, social science, psychology, biology--and yes, marketing--have spilled much ink defining what it means to be human.