Contrary to what many of my friends believe, good academics are always working--at least in the sense that when we're stuck on a problem, which is most of the time, it's impossible to leave it behind. A worthwhile problem is a brainworm: it stays with you until it's resolved or replaced by another one. My Dartmouth colleague Luke Chang, a neuroscientist who studies what happens in people's heads when we communicate, is no stranger to this affliction. One day, on a long drive back to Hanover, he found himself preoccupied with such a worm. The drive up I-89 is usually uneventful--a straight shot north, ideal for letting your mind off the leash. But Luke's mind snagged on a technical challenge: how to turn a decent model of facial expression into something truly convincing. The aim was to encode the various nuanced ways human faces transmit states of mind, and then to visualize them; smiles and frowns are the barest beginning. The spectrum of human emotions and intentions is embodied in a range of expressions which serve as a basic alphabet for communication.

The Herculaneum Scrolls contain hugely significant philosophical and literary texts from ancient Greek and Roman scholars, but were turned to carbonized lumps by the catastrophic eruption of Mount Vesuvius in AD 79. Attempts to unroll the scrolls have damaged or destroyed them, turning the precious coal-like relics to dust. Now, scientists are using clever scanning techniques to identify the text written within – without having to unroll the fragile'papyrus' pages. The team has already read one of the scrolls to discover how Greek philosopher Plato spent his last evening 2,500 years ago - but say other huge revelations about Socrates could be in store. Graziano Ranocchia, a papyrologist from the University of Pisa in Italy, said: 'Plato is just the start'.

An Italian researcher has claimed to have found the long-lost burial place of the famed Greek philosopher Plato who died around 348 BC. Graziano Ranocchia used AI to decipher the Herculaneum scrolls, charred papyrus found buried by the Mount Vesuvius eruption in 79AD, revealing new text that pointed to an exact location in Athens. The analysis showed Plato was buried in'The Academy,' a famous school founded by the philosopher in 387 BC, near the so-called Museion - a small building sacred to the Muses that no longer stands among the ruins. Ranocchia and his team uncovered 1,000 words, corresponding to 30 percent of the text, using the'bionic eye' - and believe they will have the papyrus completely analyzed by 2026. The analysis showed Plato was buried in'The Academy,' a famous school founded by the philosopher in 387 BC, near the so-called Museion - a small building sacred to the Muses The team uncovered 1,000 words, corresponding to 30 percent of the text, using the'bionic eye' - and believe they will have the papyrus completely analyzed by 2026 'Compared to previous editions, there is now an almost radically changed text, implying a number of new and concrete facts about various academic philosophers,' Ranocchia said in a statement.

Large language models (LLMs) can be used to serve as agents to simulate human behaviors, given the powerful ability to understand human instructions and provide high-quality generated texts. Such ability stimulates us to wonder whether LLMs can simulate a person in a higher form than simple human behaviors. Therefore, we aim to train an agent with the profile, experience, and emotional states of a specific person instead of using limited prompts to instruct ChatGPT API. In this work, we introduce Character-LLM that teach LLMs to act as specific people such as Beethoven, Queen Cleopatra, Julius Caesar, etc. Our method focuses on editing profiles as experiences of a certain character and training models to be personal simulacra with these experiences. To assess the effectiveness of our approach, we build a test playground that interviews trained agents and evaluates whether the agents \textit{memorize} their characters and experiences. Experimental results show interesting observations that help build future simulacra of humankind.

Large language models (LLMs) have demonstrated impressive impact in the field of natural language processing, but they still struggle with several issues regarding, such as completeness, timeliness, faithfulness and adaptability. While recent efforts have focuses on connecting LLMs with external knowledge sources, the integration of knowledge bases (KBs) remains understudied and faces several challenges. In this paper, we introduce KnowledGPT, a comprehensive framework to bridge LLMs with various knowledge bases, facilitating both the retrieval and storage of knowledge. The retrieval process employs the program of thought prompting, which generates search language for KBs in code format with pre-defined functions for KB operations. Besides retrieval, KnowledGPT offers the capability to store knowledge in a personalized KB, catering to individual user demands. With extensive experiments, we show that by integrating LLMs with KBs, KnowledGPT properly answers a broader range of questions requiring world knowledge compared with vanilla LLMs, utilizing both knowledge existing in widely-known KBs and extracted into personalized KBs.

If Socrates was the wisest person in Ancient Greece, then large language models must be the most foolish systems in the modern world. In his Apology, Plato tells the story of how Socrates's friend Chaerephon goes to visit the oracle at Delphi. Chaerephon asks the oracle whether there is anyone wiser than Socrates. The priestess responds that there isn't: Socrates is the wisest of them all. At first, Socrates seems puzzled.

In this paper, we propose a SOCratic model for Robots Approaching humans based on TExt System (SOCRATES) focusing on the human search and approach based on free-form textual description; the robot first searches for the target user, then the robot proceeds to approach in a human-friendly manner. In particular, textual descriptions are composed of appearance (e.g., wearing white shirts with black hair) and location clues (e.g., is a student who works with robots). We initially present a Human Search Socratic Model that connects large pre-trained models in the language domain to solve the downstream task, which is searching for the target person based on textual descriptions. Then, we propose a hybrid learning-based framework for generating target-cordial robotic motion to approach a person, consisting of a learning-from-demonstration module and a knowledge distillation module. We validate the proposed searching module via simulation using a virtual mobile robot as well as through real-world experiments involving participants and the Boston Dynamics Spot robot. Furthermore, we analyze the properties of the proposed approaching framework with human participants based on the Robotic Social Attributes Scale (RoSAS)

While ChatGPT's primary purpose is to assist users in generating human-like text, it has also made significant contributions to the field of philosophy. This, in turn, has had a significant impact on educational assessment, enabling educators to evaluate students' critical thinking skills in new and exciting ways. The doomsayers, by contrast, are sceptical. Here at UCC, for example, I've heard more than a few colleagues echoing Socrates, who, in Plato's dialogue Phaedrus (370 BC), expresses similar worries about the invention of … wait for it … writing. "This invention will produce forgetfulness in the minds of those who learn to use it ... you offer your pupils the appearance of wisdom, not true wisdom, for they will read many things without instruction and will therefore seem to know many things, when they are for the most part ignorant and hard to get along with since they are not wise, but only appear wise."

Do you run a software company looking to reach an audience of early-adopters? For the past few weeks, I've been using GPT-3 to help me with personal development. I wanted to see if it could help me understand issues in my life better, pull out patterns in my thinking, help me bring more gratitude into my life, and clarify my values. I've been journaling for 10 years, and I can attest that using AI is journaling on steroids. To understand what it's like, think of a continuum plotting levels of support you might get from different interactions: Talking to GPT-3 has a lot of the same benefits of journaling: it creates a written record, it never gets tired of listening to you talk, and it's available day or night.

One particularly interesting aspect of these models is that their behavior can be configured by a prompt, the initial text provided to the model, which establishes a pattern that the model attempts to continue. General purpose Large Language models can be fine-tuned on specific corpora to provide expertise in a particular domain. One such model is the OpenAI Codex model [3], a 12 billion parameter version of GPT-3 [2, 11], fine-tuned on code samples from 54 million public software repositories on GitHub. This model powers Github Co-Pilot [5], which primarily provides code-completion services within an Integrated Development Environment. We wondered whether such a model could power a conversational programming assistant and perhaps approach the vision laid out by Rich and Waters for their Programmer's Apprentice [15]. We developed the Programmer's Assistant prototype to explore this possibility, and to test whether potential users would find this sort of system useful and desirable [16]. In this paper we will review the steps taken to engineer the prompt for the Programmer's Assistant that used the Codex model to power an interactive conversational assistant, and how we evolved the prompt to establish the desired persona and behavior.