Artificial Cognition RSS

Artificial Cognition, Microsoft Copilot -

Microsoft 365’s AI-powered Copilot is like an omniscient version of Clippy

Microsoft 365’s AI-powered Copilot is like an omniscient version of Clippy

Each of the former Office apps will get AI-assisted automation features Today Microsoft took the wraps off of Microsoft 365 Copilot, its rumored effort to build automated AI-powered content-generation features into all of the Microsoft 365 apps. The capabilities Microsoft demonstrated make Copilot seem like a juiced-up version of Clippy, the oft-parodied and arguably beloved assistant from older versions of Microsoft Office. Copilot can automatically generate Outlook emails, Word documents, and PowerPoint decks, can automate data analysis in Excel, and can pull relevant points from the transcript of a Microsoft Teams meeting, among other features. Microsoft is currently testing Copilot "with 20 customers, including eight in Fortune...

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Artificial Cognition, Mind Reading -

Mind Reading For Brain-To-Text Communication!

High-performance brain-to-text communication via imagined handwriting   Brain-computer interfaces (BCIs) can restore communication to people who have lost the ability to move or speak. To date, a major focus of BCI research has been on restoring gross motor skills, such as reaching and grasping1–5 or point-and-click typing with a 2D computer cursor6,7. However, rapid sequences of highly dexterous behaviors, such as handwriting or touch typing, might enable faster communication rates. Here, we demonstrate an intracortical BCI that can decode imagined handwriting movements from neural activity in motor cortex and translate it to text in real-time, using a novel recurrent neural network...

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Artificial Cognition, GPT-4, OpenAI -

The Model That Changes Everything: Alpaca Breakthrough (ft. Apple's LLM, BritGPT, Ernie and AlexaTM)

        8 years of cost reduction in 5 weeks: how Stanford's Alpaca model changes everything, including the economics of OpenAI and GPT 4. The breakthrough, using self-instruct, has big implications for Apple's secret large language model, Baidu's ErnieBot, Amazon's attempts and even governmental efforts, like the newly announced BritGPT.   I will go through how Stanford put the model together, why it costs so little, and demonstrate in action versus Chatgpt and GPT 4. And what are the implications of short-circuiting human annotation like this?   

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Artificial Cognition, Digital Minds -

Should AI Research Try to Model the Human Brain?

                    Reinforcement Learning, Fast and Slow Recent AI research has given rise to powerful techniques for deep reinforcement learning. In their combination of representation learning with reward-driven behavior, deep reinforcement learning would appear to have inherent interest for psychology and neuroscience. One reservation has been that deep reinforcement learning procedures demand large amounts of training data, suggesting that these algorithms may differ fundamentally from those underlying human learning. While this concern applies to the initial wave of deep RL techniques, subsequent AI work has established methods that allow deep RL systems...

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Artificial Cognition, MLLM -

NVIDIA's New AI: Better AI Videos Are Here!

Abstract     Generating Long Videos of Dynamic Scenes       We present a video generation model that accurately reproduces object motion, changes in camera viewpoint, and new content that arises over time. Existing video generation methods often fail to produce new content as a function of time while maintaining consistencies expected in real environments, such as plausible dynamics and object persistence. A common failure case is for content to never change due to over-reliance on inductive biases to provide temporal consistency, such as a single latent code that dictates content for the entire video. On the other extreme,...

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