Rosalind Franklin Institute’s Post

Narayan Dharel MD, PhD, FACG thankyou for this insightful session.

2 min video on the solutions and interventions we need to tackle the societai challenge of #endocrinedisruptors together with Dr. Nicos Skordis https://lnkd.in/d5U7A4Nb

When you see such magnificent, detailed landscapes in Aurion, Legacy of the Kori-odan, doesn't it make you want to play?  What are you waiting for to play this masterpiece? It's available here: https://lnkd.in/eNAuAtGt #aurion #aurionverse #xbox

thank you for everything " Time travel is the hypothetical ability to travel to the past or future. It's a common theme in fiction, especially science fiction, and has been depicted in many media forms since the late 19th century. In fiction, time travel is often achieved by using a time machine, and stories often focus on the consequences of changing history. However, no one has ever demonstrated the ability to travel through time as depicted in science fiction. According to Albert Einstein's theories of relativity, it's possible to travel into the future by traveling at speeds close to the speed of light or spending time in an intense gravitational field. However, traveling into the past is considered very difficult or impossible. Some scientists believe that cosmic strings could be used to create a closed timelike curve, which could theoretically allow a spaceship to travel back in time. However, this is highly speculative, and would require a loop of string that contained half the mass-energy of an entire galaxy. Another theory is that rotating lasers could be used to travel back in time. Ronald Mallett's prototype laser loop bends time, which could hypothetically allow movement back to the moment the machine was turned on. "

I'm excited to share about the good work from my colleagues and collaborators from Taiwan Tshing Hua Univ https://lnkd.in/g2dHAAic Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow Abstract Existing Maximum-Entropy (MaxEnt) Reinforcement Learning (RL) methods for continuous action spaces are typically formulated based on actor-critic frameworks and optimized through alternating steps of policy evaluation and policy improvement. In the policy evaluation steps, the critic is updated to capture the soft Q-function. In the policy improvement steps, the actor is adjusted in accordance with the updated soft Q-function. In this paper, we introduce a new MaxEnt RL framework modeled using Energy-Based Normalizing Flows (EBFlow). This framework integrates the policy evaluation steps and the policy improvement steps, resulting in a single objective training process. Our method enables the calculation of the soft value function used in the policy evaluation target without Monte Carlo approximation. Moreover, this design supports the modeling of multi-modal action distributions while facilitating efficient action sampling. To evaluate the performance of our method, we conducted experiments on the MuJoCo benchmark suite and a number of high-dimensional robotic tasks simulated by Omniverse Isaac Gym. The evaluation results demonstrate that our method achieves superior performance compared to widely-adopted representative baselines.

Thank you for the insightful comment on our last post! I couldn't agree more on the importance of complementing different classification techniques, both for individual satellites and across various sensors. This approach indeed helps to better correlate results and identify the areas with the highest potential more accurately. At Four Point, we are committed to pushing the boundaries of satellite image analysis in mineral exploration. Our platform (TerraEye) not only integrates multispectral and hyperspectral data but also combines Digital Elevation Models (DEMs) and auto-detected lineaments into a cohesive Digital Twin. This allows us to provide a more comprehensive and accurate representation of the geological landscape. 🌍🔍 🚀 Exciting Updates: - We are soon rolling out new functionalities that will further enhance your exploration capabilities. ✨ - Stay tuned for our upcoming demos showcasing these powerful new features. 📊 🌟 Special Offer: Now is the perfect time to take advantage of our development pricing: $50 & $99 Monthly Plans: Get started with our extended exploration subscription. 💸 Free Month: Enjoy a free month of standard exploration. 🎁 Future Savings: Early subscribers will benefit from the best deals when our prices go up in Q4, and you'll get exclusive discounts on future reports! 🏷️ Don't miss out on this opportunity to leverage the latest advancements in satellite-derived analytics. Join us now and be part of the revolution in mineral exploration! 🚀 app.terraeye.co

Finally a serious tool. After over 10 years of study and practice with in-depth studies in the planetarium, this indicator, Optuma Astro by Mr Alraie and his team, brings together everything I have researched over many years. I recommend it to those who want to trade professionally and to those who use Ganzilla. Implemented: conjunctions, oppositions, trines, squares, sextiles, quinquonces. Sincere compliments.

6 more patents filed in the year 2023 with multiple in Offensive category !! "The passion for invention will never die." Carl Benz, a man ahead of his time, believed in the potency of his invention. So do we! Congratulations and Thank you Narayan Kumar Saraf, Parthasarathi Bhattacharya, Abhiraj Khare, Vijesh Pachatiyan, Anil Upadhyay, Ansh Taneja, Manoj, Nandini Prabhu, Himanshi Saini, Satyam Lama. Details: Co-Inventor: NaSa (Narayan Saraf) 1. System for Intelligent Support from Vehicle Companion Object (Drone) 2. Multi-Threaded Support from Intelligent and Automated Vehicle Companion Object (Drone) Co-Inventors: Parthasarathi Bhattacharya (He/Him), Abhiraj Khare, Anil U. 3. System for unidirectional communication among independent child modules in Modular Architecture Co-Inventors: Abhiraj Khare, Vijesh Pachatiyan 4. Protective Structured Data Export-Import on Mobile Devices Co-Inventors: MANOJKUMAAR GOWDA, Vijesh Pachatiyan 5. Algorithm to identify the key flow for app’s data analytics Co-Inventor: Ansh Taneja 6. A Method for Vehicle SOS with Radio Communication

The comparison of Twitter’s massive staff cuts under Elon Musk to government bureaucracy highlights the challenges of efficiency and restructuring in large organizations. While private companies may quickly adapt and streamline, government systems are often deeply entrenched in bureaucracy, making such drastic changes nearly impossible. This raises questions about the balance between functionality, accountability, and adaptability in public versus private sectors. Throughout history, there have been notable successes and failures in restructuring large organizations. Singapore’s civil service reform under Lee Kuan Yew transformed a corrupt and inefficient bureaucracy into one of the most efficient in the world through meritocracy and performance-based systems. In contrast, General Motors’ failed restructuring in the 2000s, plagued by legacy costs and market missteps, led to its bankruptcy despite government intervention. Similarly, Apple’s turnaround under Steve Jobs showcased how decisive leadership and a focus on innovation can save a struggling company, making it a global leader. On the other hand, the Soviet Union’s attempts at restructuring through Perestroika revealed the dangers of rigid bureaucracies resisting change, ultimately accelerating its collapse. These cases highlight the critical role of visionary leadership, adaptability, and addressing systemic inefficiencies in achieving successful reform, while failures often stem from resistance to change and poor execution. #Leadership #Restructuring #Bureaucracy #Innovation #CivilServiceReform #CorporateTurnaround #EconomicCollapse #HistoricalLessons #OrganizationalChange

A great intuitive introduction on diffusion models with pytorch hands-on. Back in the days into markovian process and statistical physics. Very useful!