![]() ![]() ![]() LLMs can be complex and unpredictable, and their responses require careful evaluation. But with great power comes great responsibility. Give my previous article a read and let me know what you think: #AIEthics #DigitalIndia #InnovationLeadership #AIRegulation #ArtificialIntelligenceĪI is revolutionizing industries across the globe, and large language models (LLMs) are at the forefront of this transformation. We’ve got to act today to be able to shape the AI future we want tomorrow! The forthcoming #DigitalIndiaBill should incorporate these safeguards to ensure responsible and ethical AI practices. It is incumbent upon us to navigate through the potential pitfalls inherent in automation-induced job displacement, the specter of deep fake manipulations, concerns about privacy incursions, copyright infringements, and of course, the question of academic integrity. We must classify tools by their perceived risks and establish a global framework for AI. In my previous writings, I have underscored the need to subject nascent AI models to rigorous evaluation prior to their deployment. But don’t worry I’ll be back!)īritish PM Sunak’s latest move on the AI regulation debate marks a positive stride forward. I got married this week! (I am planning to take some time off to fully enjoy this time. PS: Some exciting news on the personal front. This technique, called NEFTune, has been shown to significantly improve performance in conversational tasks, and it does so without compromising knowledge in question-answer tasks. present a simple and straightforward method to enhance the performance of language models: the injection of uniform random noise into token embeddings. In their paper NEFTune: Noisy Embeddings Improve Instruction Finetuning, Jain, Chiang, Wen, Kirchenbauer et al. They employed distilled Direct Preference Optimization (DPO), which is much less complex than Reinforcement Learning with Human Feedback (RLHF). Zephyr: Direct Distillation of LM Alignment presents a fresh approach to training language models, showcasing the Zephyr 7B model's remarkable performance in both conversational and knowledge benchmarks. This surprisingly good performance may be largely attributed potentially to its unique training data. ![]() The Mistral 7B paper introduces a compact yet powerful language model that, despite its relatively modest size of 7 billion tokens, outperforms its larger counterparts, such as the 13B Llama 2 model, in various benchmarks. invest significant computational resources to conduct a thorough comparison between Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs), challenging the prevailing notion that ViTs outperform CNNs in image classification tasks. ![]() In the paper ConvNets Match Vision Transformers at Scale, Smith et al. I tried to summarize and discuss the noteworthy things here: Ī snapshot of the highlights I am covering in this article: ❧a/n: I’m not so good with social media au’s but I fell in love with Jun that it inspired me to create this and he deserve it so muchĬhaper 23: This was never meant to happened…Ĭhaper 25: I just wanna get over this shitĬhapter 29: Will you go on a date with me.From Vision Transformers to innovative large language model finetuning techniques, the AI community has been very active with lots of interesting research this past month. ❧Summary: When Minghao had no choice and let the two of his friends meet which somehow got along and clicked then suddenly comes a huge change in Y/n’s part… ❧Warning(s): Lots of Swearing, Stalking, Threats and etc… ❧Genre: college au, fluff, crack, social media au, a bit angst? ❧Main Pairing: Junhui x female!reader insert ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |