Date: 2025-08-21 Page is: DBtxt003.php txt00026804
ECONOMIC COMMENTARY
CHRIS MACRAE
Chris Macrae: will youth ever be sustainability generation? ed3 AIgames.solar Bard.solar
CHRIS MACRAE
Chris Macrae: will youth ever be sustainability generation? ed3 AIgames.solar Bard.solar
Original article: https://www.linkedin.com/pulse/afore-tuesday-ai-korea-kingc-world-leaders-gemini-74-chris-2apme/
Peter Burgess COMMENTARY
Peter Burgess
==================
breaking news - for first time, whole of usa not just west coast is transforming edu around youth agency, case 1 national school redesign; case 2 Youth Mental Health Corps -mail me chris.marae@yahoo.couk to discuss more details and helping these movements scale over next 12 months case 1 National School Redesign - Bloomberg John Hopkins
see national school redesign annual showcase 2023-24 out of bloomberg johns hopkins campus on doorsteps (well 5 minute walk) from congress
================================================== case 2 youth mental health corps -
miraculously out of gov's americorps this was launched yesterday at axios washington DC (notably their weekly health letter), spotify, a seattle family foundation (schultz), americorps;
bonus question: can this leverage breakthrough lancet has been arguing ; pre-teens up need peer to peer support on next health challenges of growing up;
===========
where to start with deep learning and nvidia
open usd & pixar\ 5 things to know since pixar open sourced usd in 2016 When you look at 16 other goals nations committed to in 2015, we need every national leader in New York September to explain what good engineers they link in to. We dont need any more of their hate speeches or excuses. At a minimum lets see who wants to schedule an ai summit that can keep up with King Charles common sense out of their nation . What else can we the peoples make sure UN Summit future September starts turning round from the current situation in which every goal promised in 2015 is actually going backwards How about we all start by sharing ideas the chats have. We need to pretrain them (where do you want to doublecheck gemini); its most imporatnt that we twin with each other; if your place is getting somethhing right, where cam you twin with a community that needs help Overall I am not sure that any of the sdgs announced in 2015 are going forward. Can you give us some examples where a least some AI leaders are progressing some sdgs? You're right, achieving all the SDGs by 2030 is a significant challenge. While progress has been uneven, there are indeed AI leaders making strides towards some SDGs. Here are some examples: SDG 3: Good Health and Well-being: DeepMind (Demis Hassabis): Developing AlphaFold, a protein structure prediction tool, which has the potential to accelerate medical research and drug discovery. IBM Watson Health: Creating AI-powered tools for healthcare providers to analyze patient data, improve diagnoses, and personalize treatment plans. ========================================= I wanted to take gemini into a deeper conversation so i used this slide from 2020 video of Jensen Huang question to gemini : Could we consider health and deep learning modes of transforming drug discovery. In a 2020 training video Jensen Huang mentions these deep learning components collectively called Nvidia Clara Discovery -how do you see these and in silico drug innovation overall - NVIDIA Clara Discovery? https://catalog.ngc.nvidia.com/orgs/nvidia/collections/claradiscovery Clara Discovery is a collection of frameworks, applications, and AI models enabling GPU-accelerated computational drug discovery. Drug development is a cross-disciplinary endeavor. Clara Discovery can be applied across the drug discovery process and combines accelerated computing, AI and machine learning in genomics, proteomics, microscopy, virtual screening, computational chemistry, visualization, clinical imaging, and natural language processing.
Gemini reply: NVIDIA Clara Discovery and In Silico Drug Discovery: A Powerful Combination
NVIDIA Clara Discovery is a valuable suite of tools for accelerating drug discovery through the power of deep learning and other AI techniques. Here's a breakdown of its potential and how it fits into the broader landscape of in silico drug innovation:
Clara Discovery's Strengths:
- Cross-disciplinary approach: It combines AI, machine learning, accelerated computing, and various life science disciplines, providing a holistic view of the drug discovery process.
- Wide range of applications: Clara Discovery supports genomics, proteomics, microscopy, virtual screening, protein structure prediction, and more, covering critical stages of drug development.
- Pre-trained models and frameworks:
- The inclusion of pre-trained models for NLP (BioMegatron, BioBert), protein structure prediction (MELD), and other tasks saves researchers time and allows them to focus on specific challenges.
- Scalability and Efficiency: By leveraging NVIDIA's GPUs, Clara Discovery enables researchers to analyze massive datasets and perform complex calculations efficiently.
- Complementary to Traditional Methods: Clara Discovery is a powerful tool that complements traditional drug discovery methods, offering faster and more cost-effective ways to identify promising drug candidates.
- Increased Success Rates: By leveraging AI for tasks like virtual screening and target identification, in silico approaches can significantly increase the likelihood of successful drug development.
- Clara Discovery is a significant advancement in in silico drug discovery. By providing researchers with a comprehensive suite of AI-powered tools, it has the potential to:
- Reduce the time it takes to bring new drugs to market.
- Lower the cost of drug development.
- Increase the success rate of drug discovery efforts.
- Identify new drug targets and lead to the development of life-saving treatments.