Large language models (LLMs) excel at text-based natural language processing tasks through creative prompt engineering and in-context learning. However, their performance on spoken language understanding (SLU) tasks relies heavily on speech-to-text conversion by an off-the-shelf automation speech recognition (ASR) system, constraining their accuracy in this setup.
Introduced in May 2023 and available on iOS 17 in September 2023, Personal Voice is a voice replicator tool designed for individuals at risk of losing their ability to speak, such as those with ALS. It creates a synthesized voice for use in FaceTime, phone calls, assistive communication apps, and in-person conversations, supporting speaking ability.
Former Prime Minister of Pakistan, Imran Khan, utilized AI to deliver a four-minute speech at a virtual rally while in prison. The AI-generated voice closely resembled his own, delivering a message of resilience and defiance against political constraints faced by his party. The rally gained over five million views despite reported internet outages. AI’s political…
This blog post serves as the conclusion to a series on training BERT from scratch. It discusses the significance of BERT in Natural Language Processing, reviews the previous parts of the series, and outlines the process of building and training a BERT model. The post emphasizes understanding the model’s inner workings and shares insights on…
The year 2023 saw significant developments in the Generative AI landscape, marked by the release of multiple LLMs and the emergence of LLMOps. While there were challenges in production, it was a year of experimentation and getting to know Generative AI. Looking ahead to 2024, the focus will likely be on successfully deploying Generative AI…
The text is a comprehensive explanation of computer simulations and their applications in understanding and predicting astronomical events. It covers various scenarios of transit phenomena, including exoplanet transits, asteroid belts’ influence, and hypothetical scenarios like simulating an exoplanet with an exomoon and detecting alien megastructures. It also highlights the advantages of simulations in scientific research.…
The paper explores training End-to-End Automatic Speech Recognition (ASR) models using Federated Learning (FL) and its impact on minimizing the performance gap with centralized models. It examines adaptive optimizers, loss characteristics, model initialization, and carrying over modeling setup from centralized training to FL.
The paper “Bootstrap Your Own Variance: Understanding Model Uncertainty with SSL and Bayesian Methods” was accepted at the Self-Supervised Learning workshop at NeurIPS 2023. It proposes BYOV, combining BYOL SSL algorithm with BBB Bayesian method to estimate model posteriors, showing that BYOV’s predictive standard deviation aligns well with a Gaussian distribution.
Multimodal datasets play a crucial role in recent AI advancements like Stable Diffusion and GPT-4. However, their design is not as researched as model architectures or training algorithms. To tackle this, DataComp introduces a testbed for dataset experiments using 12.8 billion image-text pairs from Common Crawl, allowing participants to create and evaluate new datasets.
A Multi-Strategy AI with Deep Reinforcement Learning has achieved victory over GPT3.5 in a Chess Match. For more details, please visit Towards Data Science.
The text outlines the challenges faced by industries without real-time forecasts and introduces the integration of MongoDB’s time series data management capabilities with Amazon SageMaker Canvas for overcoming these challenges. It details the solution architecture, prerequisites, and step-by-step processes for setting up the solution using MongoDB Atlas and Amazon SageMaker Canvas. The post concludes with…
The text describes the concept and process of building stacked ensembles in machine learning using H2O.ai and Optuna. The author outlines the steps involved in training a stacked ensemble, including the training of base models such as Deep Neural Networks, XGBoost, and LightGBM, and subsequently training the meta-model using H2OStackedEnsembleEstimator. The summary provides an in-depth…
The text discusses the comparison between intuition and code implementation for ABC with Particle Swarm Optimization to identify its superior performance. For more information, please visit Towards Data Science.
World models are AI systems aiming to understand and predict events in an environment. The Gen-2 video generative system is an early attempt but struggles with complex tasks. Challenges include creating accurate environment maps and simulating human behavior. Researchers work to improve adaptability and capabilities through metrics, with the goal of better simulating real-world scenarios.
A new method called COLMAP-Free 3D Gaussian Splatting (CF-3DGS) has been introduced by researchers from UC San Diego, NVIDIA, and UC Berkeley. It synthesizes views using video’s temporal continuity and explicit point cloud representation without the need for Structure-from-Motion (SfM) preprocessing. CF-3DGS optimizes camera pose and 3DGS jointly, making it suitable for video streams or…
Some LLMs may produce inaccurate responses due to hallucinations. Google DeepMind researchers propose FunSearch, a method to address this issue. It combines a pre-trained LLM with an evaluator to discover new knowledge by evolving low-scoring programs into high-scoring ones. This iterative process has significant potential for real-world applications and aims to expand functionalities to tackle…
Pennsylvania congressional candidate Shamaine Daniels is utilizing an AI robocaller, Ashley, to communicate with prospective voters in multiple languages. Ashley allows for two-way communication, answering questions about Daniels’ campaign and policies. The use of AI in political outreach raises questions about regulation and accountability, as AI technology continues to advance rapidly.
OpenAI’s Superalignment project aims to prepare for the possibility of AI smarter than humans in 10 years. The team’s experiment using GPT-2 to train GPT-4 showed weaker models can guide stronger ones, but also limit their performance. OpenAI seeks solutions to supervising potential superintelligent AI to avoid adverse outcomes. This project involves significant resources and…
Artificial intelligence has made significant strides in 2023, particularly in the medical field. Some notable models include Med-PaLM 2, Bioformer, MedLM, RoseTTAFold, AlphaFold, and ChatGLM-6B. These models show promise in transforming medical processes, from providing high-quality medical answers to predicting protein structures. Researchers continue to assess and fine-tune these models for safe deployment in critical…
MIT researchers delved into deep neural networks to explore the human auditory system, aiming to advance technologies like hearing aids and brain-machine interfaces. They conducted a comprehensive study on these models, revealing parallels with human auditory patterns. The study emphasizes training in noise and task-specific tuning, showing promise for developing more effective auditory models and…