Numerous entries in the field of AI focus on generative models that extend beyond text and artwork generation. Specifically, they delve into the realm of producing human-like voices and music. This raises the question: Is voice generation the next frontier for AI? Google’s AudioPaLM offers a compelling glimpse into the direction AI is taking. AudioPaLM combines speech recognition, speech synthesis, and language modeling, indicating a potential path forward. An emerging concern revolves around training AI on data generated by AI itself. With limited input from real humans, the phenomenon of “model collapse” emerges, potentially resulting in subpar outputs.
AI also extends its influence to robotics, as exemplified by RoboCat. Unlike traditional robots programmed for specific tasks, RoboCat possesses the ability to acquire new skills post-deployment. Its learning process accelerates as it accumulates knowledge.
Another notable development is AudioPaLM, a novel language model by Google. This substantial model excels in comprehending and generating voice, bridging the gap between text and spoken language.
Voicemod, on the other hand, represents a tool that transforms human speech into AI-generated speech in real-time. It offers a variety of customizable “sonic avatars.”
In the realm of AI prompting techniques, “tree-of-thought” extends the concept of “chain-of-thought” by encouraging language models to consider multiple reasoning paths when generating outputs.
Facebook/Meta has introduced Voicebox, a generative speech model that claims to outperform its counterparts. However, they have not released an open-source version, but the associated paper outlines methods to distinguish between generated and human speech.
The EU’s draft proposal for regulating AI is summarized succinctly in the MIT Technology Review. This proposal is expected to undergo a legislative process taking at least two years.
OpenLLM supports the deployment of various open-source large language models in production. It also promises future integration with tools like Bento, with support for Langchain on the horizon.
Infinigen serves as a photorealistic 3D scene generator for natural-world environments. It produces synthetic training data for AI systems, including terrains, flora, fauna, and weather patterns, with the potential for adding built objects in the future.
Facebook/Meta introduces I-JEPA, a large model designed for efficiency and inspired by human cognitive processes. It represents a step towards realizing Yann Lecun’s vision of next-generation artificial intelligence.
MusicGen, another creation from Facebook/Meta, showcases a generative model for music. While it demonstrates a convincing ability to compose music, its capacity to transcend established musical cliches remains uncertain.
OpenAI has introduced a “function calling” API that enables applications to describe functions to the model. When required, GPT can return a JSON object describing the function call, allowing the application to execute the function and relay the result to the model.
A study highlights the use of AI by AWS Mechanical Turk workers in generating or labeling training data for AI systems. This development raises questions about its impact on future AI generations.
The repercussions of training generative AI systems on data they themselves have produced are explored. Instances like Copilot being trained on code generated by Copilot or GPT-4 on web content created by GPT-4 lead to “model collapse,” resulting in reduced output quality.
FrugalGPT proposes a cost-effective approach to utilizing large language models like GPT-4 by employing a pipeline of models, refining prompts at each stage, and leveraging free or inexpensive models for most processing tasks.
DeepMind’s AlphaDev employs AI to expedite sorting algorithms, working at the assembly language level. The code is subsequently converted back to C++ and incorporated into the C++ standard library via the LLVM project.
An artist utilizes Stable Diffusion to craft functional QR codes that also double as artistic creations, which are shared on Reddit.
The regulation of AI can learn valuable lessons from nuclear non-proliferation, emphasizing traceability and transparency through initiatives like Model Cards and Datasheets for Datasets.
Sam Altman discusses ChatGPT’s plans, highlighting the current compute limitations that hinder features like custom fine-tuning, expanded context windows, and multimodality.
Facebook/Meta introduces LIMA, a 65B parameter language model fine-tuned on a select set of prompts and responses without reinforcement learning with human feedback (RLHF).
Gandalf presents a prompt injection game, challenging users to coax AI into revealing its password.
In the realm of programming, Leptos emerges as a new open-source, fully typed web framework for Rust.
WebAssembly may potentially replace containers in the near future, offering portability and compactness.
Adam Jacob explores the revitalization of DevOps with insights drawn from multiplayer games and digital twins.
Alex Russell emphasizes the need for improving web performance for users with midrange or low-end smartphones, suggesting that excessive JavaScript can hinder performance on many websites.
Doug Crockford advocates for transitioning from JavaScript to newer, more advanced programming languages.
Wing, a novel programming language, introduces high-level abstractions tailored for cloud-native program development, aiming to facilitate AI code generation for cloud-native applications.
Simpleaichat simplifies the process of writing programs that utilize GPT 3.5 or GPT 4 through a Python package.
StarCoder and StarCoderBase constitute an open-source language model for software development, akin to Codex. They were trained on a vast collection of permissively licensed GitHub repositories, including inspection tools and an opt-out process.
Measuring developer experience involves considering not only technical metrics but also personal factors like developer satisfaction and daily friction.
OpenChat, an open-source chat console, allows customization and connection to large language models, currently supporting GPT-* and featuring unlimited memory through PineconeDB.
WebAssembly holds promise in enhancing runtime performance and latency across various environments, including browsers, Kubernetes clusters, and edge devices.
The concept of software-defined cars prompts reevaluation of security measures, as it introduces new opportunities and potential risks.
LQML introduces a programming language designed for interacting with language models, offering a structured approach for communication with AI systems.
Memory Spy, a web application created by Julia Evans, allows users to explore C program memory representation, offering insights into software functionality.
In the realm of augmented and virtual reality, David Pogue reviews Apple Vision, an expensive AR headset with limited but impressive capabilities.
Apple’s challenge with the Vision Pro goggles lies in encouraging developers to create compelling 3D applications that truly leverage the potential of AR/VR.
Tim Bray’s post delves into the essence of augmented reality and its implications for software developers, emphasizing the need for innovative approaches beyond Apple Vision.
Hachette explores the metaverse with “Beyond the Pages,” targeting a younger audience with immersive experiences.
In the realm of security, organizations are urged to focus on fundamental practices like access controls, robust passwords, multi-factor authentication, zero trust, penetration testing, and robust backup strategies to combat the rising threat of faster ransomware attacks.
Cloud systems are increasingly vulnerable to attacks due to misconfigured identity and access management, necessitating rigorous adherence to basic security practices.
AI Package Hallucination introduces a novel malware distribution technique that exploits AI-generated package recommendations.
In the domain of the web, a new standard enables NFTs to contain wallets, facilitating collections of related resources for various purposes.
The W3C introduces a secure payment confirmation standard aimed at simplifying and securing online checkout processes.
Tyler Cowen predicts that cryptocurrencies will play a crucial role in facilitating transactions between AI systems, given the limitations on AI entities having bank
accounts.
Web and mobile performance optimization remains an under-discussed topic, with a focus on improving Wikipedia performance by eliminating unnecessary JavaScript.
