Indian court legal texts and processes are essential towards the integrity of the judicial system and towards maintaining the social and political order of the nation. Due to the increase in number of pending court cases, there is an urgent need to develop tools to automate many of the legal processes with the knowledge of artificial intelligence. In this paper, we employ knowledge extraction techniques, specially the named entity extraction of legal entities within court case judgements. We evaluate several state of the art architectures in the realm of sequence labeling using models trained on a curated dataset of legal texts. We observe that a Bi-LSTM model trained on Flair Embeddings achieves the best results, and we also publish the BIO formatted dataset as part of this paper.

Researchers often rely on humans to code (label, annotate, etc.) large sets of texts. This kind of human coding forms an important part of social science research, yet the coding process is both resource intensive and highly variable from application to application. In some cases, efforts to automate this process have achieved human-level accuracies, but to achieve this, these attempts frequently rely on thousands of hand-labeled training examples, which makes them inapplicable to small-scale research studies and costly for large ones. Recent advances in a specific kind of artificial intelligence tool - language models (LMs) - provide a solution to this problem. Work in computer science makes it clear that LMs are able to classify text, without the cost (in financial terms and human effort) of alternative methods. To demonstrate the possibilities of LMs in this area of political science, we use GPT-3, one of the most advanced LMs, as a synthetic coder and compare it to human coders. We find that GPT-3 can match the performance of typical human coders and offers benefits over other machine learning methods of coding text. We find this across a variety of domains using very different coding procedures. This provides exciting evidence that language models can serve as a critical advance in the coding of open-ended texts in a variety of applications.

Sign up to receive our weekly newsletter of the best New Yorker podcasts. Sam Altman, the C.E.O. of OpenAI, which created ChatGPT, says that artificial intelligence is a powerful tool that will streamline human work and quicken the pace of scientific advancement. But ChatGPT has both enthralled and terrified us, and even some of A.I.'s pioneers are freaked out by the technology and how quickly it has advanced. David Remnick talks with Altman, and with the computer scientist Yoshua Bengio, who won the prestigious Turing Award for his work in 2018, but recently signed an open letter calling for a moratorium on some A.I. research until regulation can be implemented. The stakes, Bengio says, are high: "I believe there is a non-negligible risk that this kind of technology, in the short term, could disrupt democracies."

On Tuesday morning, the merchants of artificial intelligence warned once again about the existential might of their products. Hundreds of AI executives, researchers, and other tech and business figures, including OpenAI CEO Sam Altman and Bill Gates, signed a one-sentence statement written by the Center for AI Safety declaring that "mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war." Those 22 words were released following a multi-week tour in which executives from OpenAI, Microsoft, Google, and other tech companies called for limited regulation of AI. They spoke before Congress, in the European Union, and elsewhere about the need for industry and governments to collaborate to curb their product's harms--even as their companies continue to invest billions in the technology. Several prominent AI researchers and critics told me that they're skeptical of the rhetoric, and that Big Tech's proposed regulations appear defanged and self-serving.

Fox News' Eben Brown reports on how more companies are using A.I. technology to set retail prices based on data-driven supply-and-demand. A new artificial intelligence (AI) tool could help African countries better track and predict crop rotations and yields, providing a key tool to help mitigate food crisis across the continent. "Relying on conventional analytic techniques alone will not deliver the effective decision-making we need to meet these challenges," Racine Ly, the director of data management for the project, told Science X. "Since this is data that researchers and decision-makers most importantly will use to make decisions, we needed to make sure that the data is correct, and the predictions are accurate," he added. AKADEMIYA2063, a research organization, said the Africa Agriculture Watch (AAgWa) tool will help prioritize and maximize the production of staple foods such as maize, cassava and sorghum. WILL AI EVER BE SMART ENOUGH TO DECIPHER FEDERAL REGULATIONS?

Sam Altman, the CEO of artificial intelligence lab OpenAI, told a Senate panel he welcomes federal regulation on the technology "to mitigate" its risks. President Biden told hundreds of U.S. Air Force Academy graduation attendees on Thursday that scientists are warning about the capabilities of artificial intelligence. "I met in the Oval Office, in my office, with 12 leading -- no, excuse me, eight leading scientists -- in the area of AI," he said, speaking at Falcon Stadium in Colorado. "Some are very worried that AI can actually overtake human thinking and planning," Biden noted. "So we've got a lot to deal with."

Companies that replaced workers with chatbots have faced high-profile stumbles. When the technology news site CNET used artificial intelligence to write articles, the results were riddled with errors and resulted in lengthy corrections. A lawyer who relied on ChatGPT for a legal brief cited numerous fictitious cases. And the National Eating Disorders Association, which laid off people staffing its helpline and reportedly replaced them with a chatbot, suspended its use of the technology after it doled out insensitive and harmful advice.

Country star Tracy Lawrence talks about his experience using AI and why he thinks there needs to be more regulations while appearing at the ACM Awards. At the heart of most talented singers is their innate ability to write meaningful music. In the country music world, there is a premium for artists who can not only sing but write their own hits, so for some country stars, the concept of artificial intelligence being used in the music industry is nonsense. "I would struggle to think something that couldn't feel could really write a song, to make somebody else feel," musician Riley Green told Fox News Digital of the threat of AI in music at the ACM Awards. "I mean, the world's always going to change. Nothing's worth freaking out over, I think is the main thing. Riley Green is wary of music written by AI, questioning how much people would be able to take away from it. AI HAS KEANU REEVES, HARRISON FORD, ELON MUSK'S EX-GIRLFRIEND GRIMES AT ODDS OVER ITS USE Nate Smith isn't exactly concerned with AI infiltrating the music scene. Other artists have fears over AI's involvement within the industry. I played around with … a little bit of the AI stuff," Tracy Lawrence told Fox News Digital.

Fox News correspondent Grady Trimble has the latest on fears the technology will spiral out of control on'Special Report.' Robots could soon be cloaked in human-like synthetic skin, similar to the cyborg assassin of the "Terminator" movie franchise, after Stanford University researchers developed an ultra-realistic, self-healing material. Researchers have been studying and developing convincing skin materials for robots for years, with Stanford professor Zhenan Bao touting the first multi-layer self-healing synthetic electronic skin back in 2012. More than a decade later, Bao and fellow researchers have taken their studies even further into the future: layers of synthetic skin that can now self-recognize and align with each other when injured, simultaneously allowing the skin to continue functioning while healing. "We've achieved what we believe to be the first demonstration of a multi-layer, thin film sensor that automatically realigns during healing," Christopher B. Cooper, Stanford Ph.D. student and co-author of the study, told SWNS.

This paper investigates the capabilities of ChatGPT as an automated assistant in diverse domains, including scientific writing, mathematics, education, programming, and healthcare. We explore the potential of ChatGPT to enhance productivity, streamline problem-solving processes, and improve writing style. Furthermore, we highlight the potential risks associated with excessive reliance on ChatGPT in these fields. These limitations encompass factors like incorrect and fictitious responses, inaccuracies in code, limited logical reasoning abilities, overconfidence, and critical ethical concerns of copyrights and privacy violation. We outline areas and objectives where ChatGPT proves beneficial, applications where it should be used judiciously, and scenarios where its reliability may be limited. In light of observed limitations, and given that the tool's fundamental errors may pose a special challenge for non-experts, ChatGPT should be used with a strategic methodology. By drawing from comprehensive experimental studies, we offer methods and flow charts for effectively using ChatGPT. Our recommendations emphasize iterative interaction with ChatGPT and independent verification of its outputs. Considering the importance of utilizing ChatGPT judiciously and with expertise, we recommend its usage for experts who are well-versed in the respective domains.