Amit Bhatnagar’s Post

Sakana AI unveils "The AI Scientist" (https://lnkd.in/d4Rgp4i2), an automated system revolutionizing machine learning research. This innovative platform conducts experiments, generates ideas, writes papers, and even conducts peer reviews autonomously, accelerating scientific discovery in the field. Key features of The AI Scientist: - Full automation of the research process - Low-cost paper production - Introduces novel contributions in diffusion models and transformers While this system shows great promise, it also comes with limitations. Personally, I remain skeptical due to the absence of reasoning abilities in LLM as of today. However, the development of such technology raises crucial ethical considerations and sparks discussions on the future of AI in scientific research. #AI #MachineLearning #Research #ArtificialIntelligence #ScientificDiscovery

AI update: Explore Sakana AI's innovative approach to transforming the field of Artificial Intelligence! https://lnkd.in/gtzMdqA5 The AI Scientist, the first comprehensive system for fully automatic scientific discovery can write scientific research papers without human intervention. Conceptual illustration of The AI Scientist. The AI Scientist first brainstorms a set of ideas and then evaluates their novelty. Next, it edits a codebase powered by recent advances in automated code generation to implement the novel algorithms. The Scientist then runs experiments to gather results consisting of both numerical data and visual summaries. It crafts a scientific report, explaining and contextualizing the results. Finally, the AI Scientist generates an automated peer review based on top-tier machine learning conference standards. This review helps refine the current project and informs future generations of open-ended ideation. #ArtificialIntelligence #Innovation #Technology #AI #SakanaAI #DigitalTransformation

The AI Scientist. Not a person but complex pipeline of trained LLMs The idea of creating a full open-ended scientific discovery system in the search for new knowledge is becoming a reality. Many of us, myself included, are still using foundational models in the small to tackle and solve very distinct and targeted problems. But what about the holy grail of knowledge creation? The AI Scientist is focused upon that endeavor. Its lofty goal is to provide a pipeline for fully automated scientific discovery culminating in the generation of the scientific paper backed by sample code, where applicable, experimentation results and automated peer review. The attached is interesting in its own right but it also very thought provoking in terms of the potential of AI agents. As an example it seems quite probable that organizations could evolve their own AI Architect, creating and feeding its agents with existing product designs and empirical data from the field in order to optimize various aspects of the design be those complexity, reliability etc. Using AI in the small is beneficial in the here and now but looking from the other side (large) shouldn’t be overlooked. https://lnkd.in/gw6bj6en

Today marks a remarkable day in AI development. Sakana Labs has introduced the world’s first AI that automates scientific research and open-ended discovery—the “AI Scientist.” This system handles every step from ideation and code writing to running experiments and producing scientific reports. Founded by former Google researchers and inspired by swarm intelligence, this development represents a significant milestone in scientific research. What does this mean for us? In addition to the impressive advancements in research, this is also a prime example of the progress being made in agent frameworks. Such frameworks enable AI systems to operate with greater autonomy and creativity, which could revolutionize the future of science and technology. What are your thoughts on this? How do you see the role of AI and agent frameworks in the future of research? I’m looking forward to hearing your perspectives! #Innovation #ArtificialIntelligence #AgentFrameworks #Research https://lnkd.in/eR-f8SSd https://lnkd.in/eCjP3N4f

The automation attack on data science is here. Sakana AI has unleashed "The AI Scientist," a revolutionary AI system that can conduct scientific research autonomously! 🤖🔬 This cutting-edge AI can generate novel ideas, write code, run experiments, analyze results, and even produce scientific papers and peer reviews—all without human intervention! Sakana AI has tested The "AI Scientist" in machine learning, and it has already published intriguing papers, demonstrating its potential to accelerate discoveries and democratize research. While the system isn't perfect and may make mistakes, it's much more cost-effective and efficient than human researchers. The creators believe this could be a game-changer for science, but they also raise concerns about the potential for AI-generated papers to flood journals or be misused. Overall, this is an exciting step towards AI-driven scientific discovery, which could transform the way we make breakthroughs in the future. What do you think about this AI scientist? Will it replace human researchers or enhance their capabilities?🤖 https://lnkd.in/g8VyTbvF #AIScientist #SakanaAI #DataScience #Innovation #FutureOfResearch

Are scientists inventing their AI replacement? https://lnkd.in/gZ6fkpd7 interesting ready - attempting to automate research itself. An end-to-end framework designed to automate the generation of research ideas, implementation, and the production of research papers.

Has Generative AI Already Peaked? | Computerphile A new paper argues that the idea that adding more data and bigger models will lead to general artificial intelligence is flawed. The paper shows that the amount of data required to achieve zero-shot performance on new tasks is astronomically vast, to the point where it cannot be achieved. The paper uses clip embeddings, which use a big vision transformer and a big text encoder to create a shared embedded space between images and text. This space can be used for classification and image recall, as well as recommender systems. However, the paper argues that these downstream tasks cannot be applied effectively for difficult problems without massive amounts of data to back them up. Specific examples, such as subspecies of a tree, require more data than is currently available. The paper's authors argue that experimentation is needed to prove that adding more data and bigger models will lead to general AI. The paper provides actual numbers, which show the trend happening or not happening, making it more interesting than a blog post that hypothesizes what will happen. #AIProgress #FutureTech #GenerativeAI #TechTrends #AIInnovation #AIAdvancements #TechDebate #AIResearch #TechDiscussion #AIInsights #TechAnalysis #FutureOfAI #AIDevelopment #TechEvolution #AIQuestioning https://lnkd.in/gBzqbryV

The Power of Humans in the Age of Artificial Intelligence Discover the undeniable value of human expertise in a world dominated by AI. Learn how humans play a critical role in analyzing data and making crucial decisions. #HumanIntelligence #AIvsHumans #DataAnalysis #DecisionMaking #HumanValue #CriticalThinking #TechnologyImpact #FutureOfWork #HumanExpertise #AIRevolution

Last week, Sakana AI introduced The AI Scientist. This is an end-to-end system for scientific discovery, powered by Large Language Models. The process automates everything from generating ideas, through to experimenting, iterating and paper writing. AI has had a significant impact on certain areas of scientific discovery, for example DeepMind's AlphaFold. However, whether The AI Scientist can provide significant contributions to scientific research is yet to be seen. And of course, the idea of removing humans from the scientific process raises many issues and concerns… #AI #science #LLM #research #aiethics https://lnkd.in/eFU3ra6c