More recently, (Fu et al., 2023) natural language processing (NLP) tasks using creates a meta-model responsible for predicting the latest generative pretrained models such as the accuracy of the LLM model using the model's GPT (OpenAI, 2023; Ouyang et al., 2022), PaLM confidence scores as features. Methods from the (Chowdhery et al., 2022), and many others (Touvron computer vision (CV) domain to assess unlabeled et al., 2023; Bai et al., 2022; Penedo et al., data more generally have, for example, proposed 2023; Taori et al., 2023). This new generation of the average threshold confidence method that learns models opens up many new possibilities including a threshold over the model's confidence, predicting competitive performance in zero-shot and few-shot accuracy as the fraction of unlabeled examples settings for tasks that have typically been modeled exceeding that threshold (Garg et al., 2022), or iteratively using a supervised setting (OpenAI, 2023). More learn an ensemble of models to identify established language models (BERT (Devlin et al., misclassified data points and perform self-training 2019), RoBERTa (Liu et al., 2019), XLM-Roberta to improve the ensemble with the identified points (Conneau et al., 2020b), etc.) provide a strong balance (Chen et al., 2021). However, the metrics and hyperparameters of inference cost and task performance for in previous works are specifically for such systems. This broad class of large language classification tasks and cannot be easily extended models (LLMs) used for complex supervised NLP to more complex tasks.

In this paper, we present StyleTTS 2, a text-to-speech (TTS) model that leverages style diffusion and adversarial training with large speech language models (SLMs) to achieve human-level TTS synthesis. StyleTTS 2 differs from its predecessor by modeling styles as a latent random variable through diffusion models to generate the most suitable style for the text without requiring reference speech, achieving efficient latent diffusion while benefiting from the diverse speech synthesis offered by diffusion models. Furthermore, we employ large pre-trained SLMs, such as WavLM, as discriminators with our novel differentiable duration modeling for end-to-end training, resulting in improved speech naturalness. StyleTTS 2 surpasses human recordings on the single-speaker LJSpeech dataset and matches it on the multispeaker VCTK dataset as judged by native English speakers. Moreover, when trained on the LibriTTS dataset, our model outperforms previous publicly available models for zero-shot speaker adaptation. This work achieves the first human-level TTS on both single and multispeaker datasets, showcasing the potential of style diffusion and adversarial training with large SLMs. The audio demos and source code are available at https://styletts2.github.io/.

Spurred by advancements in scale, large language models (LLMs) have demonstrated the ability to perform a variety of natural language processing (NLP) tasks zero-shot -- i.e., without adaptation on downstream data. Recently, the debut of ChatGPT has drawn a great deal of attention from the natural language processing (NLP) community due to the fact that it can generate high-quality responses to human input and self-correct previous mistakes based on subsequent conversations. However, it is not yet known whether ChatGPT can serve as a generalist model that can perform many NLP tasks zero-shot. In this work, we empirically analyze the zero-shot learning ability of ChatGPT by evaluating it on 20 popular NLP datasets covering 7 representative task categories. With extensive empirical studies, we demonstrate both the effectiveness and limitations of the current version of ChatGPT. We find that ChatGPT performs well on many tasks favoring reasoning capabilities (e.g., arithmetic reasoning) while it still faces challenges when solving specific tasks such as sequence tagging. We additionally provide in-depth analysis through qualitative case studies.

OpenAI's investors are making efforts to bring back Sam Altman, the chief executive who was ousted Friday, said people familiar with the matter, the latest development in a fast-moving chain of events at the artificial-intelligence company behind ChatGPT. Altman is considering returning but has told investors that he wants a new board, the people said. He has also discussed starting a company that would bring on former OpenAI employees, and is deciding between the two options, the people said.

Sam Altman always insisted that he wasn't the most important person at OpenAI despite being its CEO. As he traveled the world this year meeting world leaders--the world's unofficial ambassador of AI--Altman would soft-pedal his role, even as he stole glances at his phone to keep up with what was happening in OpenAI's luxe San Francisco offices. "We have an incredibly great team here that can do a lot of things, so mostly, I defer to them," he told me in May when I asked him how the company ran in his absence. "But some things only a CEO can do--some HR thing of the moment, or you have to kill some project, or something with a major partner." Those items would accumulate on his phone and at the end of the day he'd bat out responses. Then he would go back to speechifying, meeting developers, and taking tea with prime ministers.

An internal memo sent to OpenAI staff on Saturday after former CEO Sam Altman's abrupt firing reiterates that "a breakdown in communication" led to the decision, not "malfeasance or anything related to our financial, business, safety, or security/privacy practices," according to Axios and The New York Times. The memo obtained by both publications was sent to employees by OpenAI's Chief Operating Officer Brad Lightcap. Speculation has been nonstop since Altman was ousted unexpectedly as CEO on Friday and dropped from the company's board of directors, with little concrete information from OpenAI itself to go on. In its announcement of the decision, the board said only that he was not "consistently candid in his communications with the board, hindering its ability to exercise its responsibilities." The board named Mira Murati, OpenAI's Chief Technology Officer, as interim CEO. In response, OpenAI's now-former president, Greg Brockman, announced he was stepping down too, tweeting, "Sam and I are shocked and saddened by what the board did today."

Last month, I interviewed Sam Altman and Mira Murati of OpenAI. Now she is taking over his job. The ouster of OpenAI's Altman, one of tech's most visible chief executives, shocked the business and tech world on Friday. It also put the company's chief technology officer, Murati, in charge of tech's biggest and most daunting job: leading the AI pioneer without disrupting life as we know it.

The crisis at artificial intelligence firm OpenAI deepened this weekend amid a reported exodus of senior staff in the wake of boss Sam Altman's mystery firing. OpenAI, the company behind the ChatGPT bot, abruptly ousted Altman on Friday for allegedly misleading the board. In a statement, it said it had lost confidence in its 38-year-old co-founder after "a deliberative review process" concluded he had not been "consistently candid in his communications", without specifying how. Shortly afterwards, Greg Brockman, the company's president, announced he had resigned. "Sam and I are shocked and saddened by what the board did today… We too are still trying to figure out exactly what happened," he wrote on X.

More details of Sam Altman's sudden ousting as CEO of OpenAI have emerged, with several senior researchers quitting the company, and executives and investors from across the industry expressing shock and confusion at what is increasingly being perceived as a board coup. Hours after Sam Altman was booted from the company by its board, Greg Brockman, another OpenAI cofounder and the company's chairman, quit in protest. Brockman later posted details of Altman's removal suggesting that the company's chief scientist, Ilya Sutskever, had orchestrated the effort to remove the CEO. Brockman's post claimed that Altman was told he was being fired by Sutskever, the company's chief scientist and a member of its board. Several accounts from inside the company suggest that a disagreement between Sutskever and Altman centered around the company's direction, and specifically its ability to build more capable AI technology safety.

Sam Altman, one of the biggest names in tech, was sacked from ChatGPT-maker OpenAI without warning.