Lifeboat Foundation

“Demonstrate That Top Financial and Tech Corporations Are Committed to Longevity”

This week two Landmark International Longevity Summits in London attracted the attention of scientists, government officials, major financial corporations, insurance companies, investment banks, and technology companies from around the world. The Landmark AI for Longevity Summit and the First International Longevity Policy and Governance Summit at King’s College London are expected to become the world-leading forums for the Longevity Industry.

Reinforcement learning (RL) is a widely used machine-learning technique that entails training AI agents or robots using a system of reward and punishment. So far, researchers in the field of robotics have primarily applied RL techniques in tasks that are completed over relatively short periods of time, such as moving forward or grasping objects.

A team of researchers at Google and Berkeley AI Research has recently developed a new approach that combines RL with learning by imitation, a process called relay policy learning. This approach, introduced in a paper prepublished on arXiv and presented at the Conference on Robot Learning (CoRL) 2019 in Osaka, can be used to train artificial agents to tackle multi-stage and long-horizon tasks, such as object manipulation tasks that span over longer periods of time.

“Our research originated from many, mostly unsuccessful, experiments with very long tasks using reinforcement learning (RL),” Abhishek Gupta, one of the researchers who carried out the study, told TechXplore. “Today, RL in robotics is mostly applied in tasks that can be accomplished in a short span of time, such as grasping, pushing objects, walking forward, etc. While these applications have a lot value, our goal was to apply reinforcement learning to tasks that require multiple sub-objectives and operate on much longer timescales, such as setting a table or cleaning a kitchen.”

Deep Knowledge Group is delighted to have supported and participated in the landmark International Longevity Policy and Governance and AI for Longevity Summits that took place on November 12th at King’s College London, which gathered an unprecedented density and diversity of speakers and panelists at the intersection of Longevity, AI, Policy and Finance. The summits were organized by Longevity International UK and the AI Longevity Consortium at King’s College London, with the strategic support of Deep Knowledge Group, Aging Analytics Agency, Ageing Research at King’s (ARK) and the Biogerontology Research Foundation. Together they managed to attract the interest of major financial corporations, insurance companies, investment banks, Pharma and Tech corporations, and representatives of international governmental bodies, organisations and embassies, as well as leading media, and featured presentations and panel discussions from top executives and directors of Prudential, Barclays Business UK, HSBC, AXA, L&G, Longevity. Capital, Longevity Vision Fund, Juvenescence, the UK Office of AI, Microsoft, NVIDIA, Babylon Health, Huawei Europe, Insilico Medicine, Longevity International UK, the Longevity AI Consortium and others.

November 14, 2019, London, UK: Deep Knowledge Group executives Dmitry Kaminksiy and Eric Kihlstrom spoke at a landmark one-day event held yesterday at King’s College London with the strategic support Deep Knowledge Group. The event united two Longevity-themed summits under the shared strategic agenda of enabling a paradigm shift from treatment to prevention and from prevention to Precision Health via the synergistic efforts of science, industry, AI, policy and governance, to enable the UK to become an international leader in Healthy Longevity.

Using a supercomputing system, MIT researchers have developed a model that captures what web traffic looks like around the world on a given day, which can be used as a measurement tool for internet research and many other applications.

Understanding web traffic patterns at such a large scale, the researchers say, is useful for informing internet policy, identifying and preventing outages, defending against cyberattacks, and designing more efficient computing infrastructure. A paper describing the approach was presented at the recent IEEE High Performance Extreme Computing Conference.

For their work, the researchers gathered the largest publicly available internet traffic dataset, comprising 50 billion data packets exchanged in different locations across the globe over a period of several years.

We face complexity, ambiguity, and uncertainty about the future consequences of cryptocurrency use. There are doubts about the positive and negative impacts of the use of cryptocurrencies in the financial systems. In order to address better and deeper the contradictions and the consequences of the use of cryptocurrencies and also informing the key stakeholders about known and unknown emerging issues in new payment systems, we apply two helpful futures studies tools known as the “Future Wheel”, to identify the key factors, and “System Dynamics Conceptual Mapping”, to understand the relationships among such factors. Two key scenarios will be addressed. In on them, systemic feedback loops might be identified such as a) terrorism, the Achilles’ heel of the cryptocurrencies, b) hackers, the barrier against development, and c) information technology security professionals, a gap in the future job market. Also, in the other scenario, systemic feedback loops might be identified such as a) acceleration of technological entrepreneurship enabled by new payment systems, b) decentralization of financial ecosystem with some friction against it, c) blockchain and shift of banking business model, d) easy international payments triggering structural reforms, and e) the decline of the US and the end of dollar dominance in the global economy. In addition to the feedback loops, we can also identify chained links of consequences that impact productivity and economic growth on the one hand, and shift of energy sources and consumption on the other hand.

Watch the full length presentation at Victor V. Motti YouTube Channel

Engineering biology is already transforming technology and science, and a consortium of researchers across many disciplines in the international Genome Project-write is calling for more discussion among scientists, policy makers and the general public to shepherd future development. In a policy forum article published in the October 18 issue of Science, the authors outline the technological advances needed to secure the transformative future of synthetic biology and express their concerns that the implementation of the relatively new discipline remains safe and responsible.

Two researchers with the University of Tennessee Institute of Agriculture are co-authors on the piece titled “Technological challenges and milestones for writing genomes: synthetic genomics requires improved technologies.” Neal Stewart and Scott Lenaghan with the UTIA departments of Plant Sciences and Food Science, respectively, join Nili Ostrov, a Ph.D. research fellow in genetics at Harvard Medical School, and 18 other leading scientists from a number of institutions and disciplines, in outlining a potential timeline for the development of what they call transformative advances to science and society.

Stewart and Lenaghan are the co-directors of the UT Center for Agricultural Synthetic Biology (CASB). Formed in 2018, Stewart says CASB is the first synthetic biology center in the world aimed specifically at improved agriculture. A professor of plant sciences in the UT Herbert College of Agriculture, Stewart also holds the endowed Racheff Chair of Excellence in Plant Molecular Genetics. Lenaghan is an assistant professor in the Department of Food Science who also holds an adjunct position in the UT Mechanical, Aerospace, and Biomedical Engineering (MABE) Department.

By and Targeting Metabesity to examine the links between metabesity, Longevity and the USA’s current health shortfalls, including low health-adjusted life expectancy (“HALE”) and the large gap between HALE and life expectancy, despite its extremely high per-capita healthcare expenditures, and to chart policy recommendations to neutralize this vast health vs wealth deficit.

€œMetabesity and Longevity: USA Special Case Study € is an 85-page open-access analytical report produced jointly by Aging Analytics Agency and Targeting Metabesity to examine the links between metabesity, Longevity and the USA €™s current health shortfalls, including low health-adjusted life expectancy ( €œHALE €) and the large gap between HALE and life expectancy, despite its extremely high per-capita healthcare expenditures, and to chart policy recommendations to neutralize this vast health vs wealth deficit.

Link to Special Case Study: https://aginganalytics.com/longevity-usa/

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Anticipation and to remain hopeful and patient in expecting a preferred future have a special place and a critical role in some moral and religious systems of faith. As a personal virtue, there are many natural, cultural, social, and educational factors that play a role in its development. However, for an economic agent and in general forward looking decision makers who follow a more secular worldview, the argument in favor of anticipation and how much it could be reasonable might be less clear. Therefore, it is worthwhile to explore when and under which circumstances we should choose anticipation. A convincing argument might be helpful. In this blog post I will build a framework based on game theory to provide a better and deeper insight.

Economists, mathematicians, and to some degree, engineers have contributed to the development of game theory. In neoclassic economics, it is assumed that each economic agent has a rational behavior. According to the prediction model based on such an assumption, decision makers, if they sell goods and services, tend to maximize profit and if they buy tend to maximize utility. In other words, people naturally seek the best and the most. Moreover, decision making is based on the principle of “predict then act”. The individual first predicts the likely consequences of choices and attribute to them utilities. In the next step, an alternative is chosen that has the best consequence or the most utility. This camp or school is often called the normative decision analysis.

Nonetheless, empirical studies on the behavior of real decision makers demonstrate that despite the prediction of rational models of choice, the individuals or economic agents, do not always follow the principle of the best and the most. In 1950s, for instance, Herbert Simon showed that when faced with uncertainty and due to lack of information about the future, there are cognitive limits to rationality such that contrary to the neoclassic economic theory, people do not make decisions rationally and logically in search of the optimal alternative. Instead they seek a combination of satisfaction and sufficing levels of utility which is also called “satisficing”. This camp or school is often called the behavioral or descriptive decision analysis. To further explain, no one can claim that in a certain decision the best alternative has been chosen, regardless of the choice criteria or the ideal level of utility. Because there is always a better alternative than the best alternative known to us now. That better alternative either exists now beyond our awareness or will appear in the future. But we never can choose it if we do not know about it. In brief, we can possibly choose from a subset of the best, the best element.

In light of the flaws of the actual decision making by humans, we tend to recognize both the pros and cons of normative and descriptive decision analysis. Pioneers of decision analysis therefore have attempted to work on a new integral school that is wise enough and take into account the natural cognitive limits. This camp or school is often called the “prescriptive” decision analysis. The aim is to educate and train better decision makers, both individually and collectively. Our approach here to the question of anticipation is also integral and prescriptive.

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