Physicists set far-more-accurate limits on speed of quantum information.
Nature’s speed limits aren’t posted on road signs, but Rice University physicists have discovered a new way to deduce them that is better — infinitely better, in some cases — than previous methods. Read More
Daily Archives: September 4, 2020
We’re entering the AI twilight zone between narrow and general AI
With recent advances, the tech industry is leaving the confines of narrow artificial intelligence (AI) and entering a twilight zone, an ill-defined area between narrow and general AI.
To date, all the capabilities attributed to machine learning and AI have been in the category of narrow AI. No matter how sophisticated. …To date there are no examples of an AGI system, and most believe there is still a long way to this threshold. …Nevertheless, there are experts who believe the industry is at a turning point, shifting from narrow AI to AGI. Read More
Low-code platforms and the democratization of AI
Tech giants like IBM and Amazon are developing products that will make it easier for people without a coding background to build apps that integrate with AI services.
Key Takeaway: Low-code and no-code platforms are seeing new life, as access to artificial intelligence and fast deployment of applications becomes increasingly critical with the popularity of Cloud-based software development. These products enable those without a coding background to more easily access the benefits of AI. Read More
Low-Code Can Lower the Barrier to Entry for AI
Organizations that want to get started quickly with machine learning may be interested in investigating emerging low-code options for AI. While low-code techniques will never completely replace hand-coded systems, they can help accelerate smaller, less experienced data science teams, as well as help with prototyping for professional data scientists.
First of all, what is low-code? Well, the phrase can mean different things to different people, and its applicability to AI is not entirely nailed down. Mainstream developers have been using low-code (or no-code) approaches to creating business and consumer applications for years, and that largely forms the basis for low-code approaches in AI. Read More
Modeling the Mental Lexicon as Part of Long-Term and Working Memory and Simulating Lexical Access in a Naming Task Including Semantic and Phonological Cues
To produce and understand words, humans access the mental lexicon. From a functional perspective, the long-term memory component of the mental lexicon is comprised of three levels: the concept level, the lemma level, and the phonological level. At each level, different kinds of word information are stored. Semantic as well as phonological cues can help to facilitate word access during a naming task, especially when neural dysfunctions are present. The processing corresponding to word access occurs in specific parts of working memory. Neural models for simulating speech processing help to uncover the complex relationships that exist between neural dysfunctions and corresponding behavioral patterns.
The Neural Engineering Framework (NEF) and the Semantic Pointer Architecture (SPA) are used to develop a quantitative neural model of the mental lexicon and its access during speech processing. By simulating a picture-naming task (WWT 6-10), the influence of cues is investigated by introducing neural dysfunctions within the neural model at different levels of the mental lexicon. Read More
MIT AGI: Cognitive Architecture (Nate Derbinsky)
‘We May Be Losing The Race’ For AI With China: Bob Work
Robert Work, who pushed hard for AI under Obama, calls for major reforms to catch up with China and Russia. His model? Adm. Rickover’s creation of the nuclear Navy in the 1950s.
The former deputy secretary of defense who launched Project Maven and jumpstarted the Pentagon’s push for artificial intelligence says the Defense Department is not doing enough. Bob Work made the case that the Pentagon needs to adopt AI with the same bureaucracy-busting urgency the Navy seized on nuclear power in the 1950s, with the Joint Artificial Intelligence Center acting as “the whip” the way Adm. Hyman Rickover did during the Cold War. Read More
Rick's Cafe AI 