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Wealth inequality today in the United States There’s been a significant hubbub about wealth inequality in the United States in the past few years, with various politicians and financial media discussing the issue. The issue has seemingly struck a nerve with many Americans; 1.7 million live viewers watched Vermont Senator Bernie Sander’s town hall on economic inequality. Townhall events don’t get that many views ever, except for presidential nominee debates. So what’s going on here? more than In my view, American citizens are beginning to realize how much more of an issue economic inequality is becoming. Market Watch that the top 1% of Americans haven’t controlled as much wealth as they do since before the great depression. Let’s take a look at some of the numbers. reports In 2015, the top 1% of Americans took home 22% of all the income in the country. In comparison, right before the Great Depression hit the top 1% of Americans took home 23.9% of all income. Meanwhile, top CEOs of tech companies continue to accumulate significantly more and more wealth. Jeff Bezos is personally worth more than $100 billion. It’s highly possible that within the next 50 years Jeff Bezos or another tech CEO of a publicly traded company could become the world’s first trillionaire (an amount so large that even my word processor marks “trillionaire” as not a real word). reportedly That’s not to say that Amazon and other large tech companies haven’t been a significant positive utility to people’s lives (although exactly how much is difficult to quantify). I’m also not saying that all wealth inequality should be eliminated. That’s what occurred in Venezuela, where everybody is equal. Equally poor. There will always be some level of wealth inequality — some people simply work harder, some people are more intelligent than others, some people are better at learning, some people are better at running businesses, some people stumble into luck, etc. My thesis is simple. I believe that biotechnology will lead to an unprecedented amount of wealth inequality in the United States, unless biotechnology is regulated. The rest of this essay will explore why I believe this, steps that can be taken to prevent such a scenario from happening, and final thoughts. How biotechnology can lead to massive wealth inequality Image from Pexels So how does biotechnology play a factor in possibly leading to unprecedented levels of wealth inequality? Let’s take a look at what is happening in the world of biotechnology, and what it will likely look like in the next 50 years. I’ll examine two factors of biotechnology: gene editing and general human longevity. For gene editing, I’m going to focus on the most recent development: CRISPR. Crispr stands for Clustered Regularly Interspaced Short Palindromic Repeats, and it is a gene editing technique that has gotten a significant amount of press over the past few years. CRISPR can be used to change any chosen letter in the DNA of an organism. That all sounds good in theory, but what does this look like in practice? There’s strong evidence that certain human traits such as intelligence and strength can be attributed, at least in part, to genetics. For example, the myostatin gene put a limit on muscles growth by limiting the size and number of muscle cells within a certain range. of this gene causes hyper-muscularity. Deletion A boy was found without myostatin, and was found to have superhuman strength: at 4.5 years old he could hold 3kg dumbbells with his arms straight out to his sides. It’s not out of the realm of possibility within the next 10 to 20 years of scientists using CRISPR to remove the myostatin gene from humans to deliberately cause muscle growth. Now imagine that a CRISPR solution is created to edit the DNA of an embryo so that, when the person grows up, that person is guaranteed to be hyper-intelligent (>130 IQ) and hyper-muscular due to removal of the myostatin gene. Likely this will only be available to the rich in the beginning due to how much is involved. Let’s say at first it costs $50,000 for a person to reliably do this to an embryo. That means only people who have that much money saved or more will be able to use CRISPR to edit their children’s genes to create innate genetic advantages in them. People in third-world countries will simply not be able to afford this. This will likely cause the gap between people in first-world countries and third-world countries to widen, as well as increase the gap between those in poverty and the top 1% in the United States. In the future, It’ll be nearly impossible for a child born in a poor family to compete in entering universities or the job market when his competition consistently has an IQ that is 30 points higher than his and can memorize information and recognize patterns much more quickly. In sports, these poor children will also not be able to compete because the competition will consistently have a significant advantage to the removal of the myostatin gene, causing a level of muscle growth that is impossible for a person with the myostatin gene to compete with. This means children from richer families will be more likely to get scholarships in universities for sports such as Football or running. Let’s now look at the longevity aspect of biotechnology, which I believe wil also play a role in increasing wealth inequality. Scientists that it will soon be possible, through biotechnological innovations, to extend a person’s lifespan beyond 120 years old. Calico is a company created by Google that aims to now believe “devise interventions that enable people to lead longer and healthier lives”. Again, this longevity solution will likely be costly in the beginning. Let’s say in the next 10 years it costs $50,000 to be able to consistently and reliably increase a person’s lifespan by 30 years. The person will be able to continue to work within that additional 30 year time-period. Bob and Joe: A thought experiment I’ve given an overview of what biotechnology will be capable of. Let’s look at some hard numbers to see how this will look like in terms of actual wealth. I’ll explore this through the parable of two men: Bob and Joe. Bob did not have his DNA edited through CRISPR because his parents could not afford it. As a result, Bob has an IQ of 100, normal muscle growth, and a life expectancy of 75 years (the average life expectancy of a male in the United States today). Bob can reasonably work well up to age 65. Joe, meanwhile, did have his DNA edited with CRISPR because his parents could afford it. His parents spent $100,000 to have his DNA edited as an embryo, and now Joe has an IQ of 135, has unparalleled levels of muscle growth, and a life expectancy of 105. Joe can reasonably work well up to age 95. Both Bob and Joe begin consistently working and investing in a stock market index fund for the S&P 500 at the young age of 25. Over the past 90 years the S&P 500 an average annual return of 10%, so I’ll use that for my calculation. has had Bob makes $65,000/year in construction and can consistently put away $1,000/month into the index fund for 40 years until he becomes too old to work. Joe, meanwhile, makes $130,000/year as an investment banker (which he has access to due to his pattern recognition and memorization abilities) and can consistently put away $2,000/month into the index fund for 70 years. Let’s see how this plays out (you can put the numbers if you want to verify them): HERE Bob, 65 years old By the time Bob is old enough that he can’t consistently work anymore, he will have $5.8 million. Not bad. Joe, 65 years old At the same age that Bob retires, Joe will still be able to continue working at full capacity. At 65, Joe has $11.6 million Bob, 95 years old Bob won’t live to be this long, and there’s a very high probability that he will be dead by the age of 75 or before. Joe, 95 years old Joe is now getting to the point where he can’t consistently work like he used to. He still has at least another 10 years ahead of him that he can look forward to. Joe has consistently been putting away $2,000/month into the stock market for 70 years. At the ripe old age of 95, Joe will have… . $208.2 million It doesn’t take a genius to see the vast difference between $208.2 million and $5.8 million. These numbers are, of course, idealized. It’s not guaranteed that the S&P 500 will return 10% annually over the next 100 years. Maybe Bob works until 70 instead of 65. But the overall point still stands: biotechnology will provide a significant advantage to the already wealthy in the United States and will likely widen the wealth gap. Bob is a stand-in for the middle class person in the United States, and Joe is a stand-in for the wealthy. In fact, it’s highly likely that I’m the end results. Say, for example, that because of Joe’s intelligence he can consistently get an 11% annual return over 70 years instead of 10%. That extra 1% difference will lead to an end amount of $360.1 million, $160 million more than before. radically underestimating It’s not difficult to see how this, playing out over several generations, can lead to massive amounts of wealth inequality. The gap will grow largest, however, between first-world countries and third-world countries. For them, it’ll be nearly impossible to compete in the global marketplace in a future where almost all of manufacturing is automated, jobs require an increasing amount of cognitive ability, and your competition not only has significantly more money but also a significantly higher cognitive ability than you do. What to do about it? Hopefully I’ve demonstrated how, over only a few generations, innovations in biotechnology can lead to an ever widening gap in wealth inequality. Now you’re thinking, what is there that can be done about this potential future problem? There are several ways that we can avoid the massive wealth inequality through biotech scenario. Note that this is by no means an exhaustive list. Regulating use of gene-editing technology If, in the future, parents can use CRISPR to grant their children superhuman abilities it will likely cause an uproar among people who are not able to afford this. One step that should be taken is regulating the use of biotechnology so that it cannot be used to provide massive inherent unfair advantages to a child, such as a guaranteed high IQ or guaranteed 150 year lifespan. Of course, there is also some difficulty in defining what exactly will lead to a massive inherent unfair advantage or not. In the future CRISPR will likely be able to completely cure genetic diseases such as sickle cell anemia, cystic fibrosis, and others. Is it an unfair advantage if some parents can guarantee that their child will never have a genetic disease and others can’t because of the cost? These are the questions that we will have to grapple with in the future. Quickly lowering the costs of biotech innovations If biotechnological innovations, such as increasing lifespan or guaranteeing no genetic diseases, are incredibly cheap then there is not as much of a need to worry about certain people getting inherent advantages and others don’t. If it costs, say, $500 to apply gene-editing to guarantee inherent advantages to a child a majority of people in the United States will be able to use this. There are several ways that this can be achieved. The first way is through research and development so that the costs go down over time. Perhaps scientists find a way to make it so that gene-editing method to guarantee no diseases is incredibly cheap. Another possible way to lower costs is for the national government to subsidize the costs of gene-editing. It is in a nation’s best interest for its citizens to have advantages over other countries, so this option is not off the table. However, there will likely be a ferocious debate about whether the government should be involved in financially supporting the biotech industry, or (either implicitly or explicitly) endorsing the industry. Final thoughts Hopefully you begin to realize the massive disruptive impact that biotechnology could have in the future. We should aim to limit the potential negative effects of biotechnology, while at the same time allowing innovation to occur. Biotechnological innovations will offer many benefits to people, and we should ensure that everybody has access to these innovations and not just a select few group of people.

How Biotechnology Could Potentially Lead To Massive Wealth Inequality

Although still not widely accepted in some countries, biotechnology has proven to push industrialized countries to attain maximum growth in the sector. Having food on our table would not have been possible were it not for this community. The World Bank sees the farm sector as a significant driver for growth in several economies, especially those where agriculture employs a massive workforce that lives within and even below the poverty threshold. agriculture Today, more and more institutions are putting a premium on efforts to spur the sector’s growth and help laborers produce food more easily. As such, the world turns to the promises of biotechnology in improving the way we live through the food we eat. A from the Food and Agriculture Organization (FAO) shows that the application of biotechnology may span in every aspect of the value chain. The study noted better performances in livestock and crops thanks to biotechnology. On livestock, the FAO said animal-related experiments across the world are going intensive on increasing growth and production; improving reproduction, selection, and breeding; and making feeds richer in nutrition. report Many biotech companies are taking on these purposes. For instance, an emerging firm with equally commendable innovative is heading toward becoming a biotech giant in several communities. Established in 2006, biotechnology firm (OTCMKTS:GRCO) was founded on the vision of benefitting as many farmers it can through its corn-to-ethanol technology. The company, later on, transitioned the application to a new model where biomass or agricultural waste is used to produce ethanol. technology Greenbelt Resources Corp. Greenbelt Resources’ waste-to-bioproduct technology enables the recycling of food, beverage and agricultural waste and their conversion into bioproducts such as bioethanol, fertilizer, a valuable amino-acid rich protein concentrate and, now, including a solvent for cannabis extraction. So far, the equipment has garnered $2.4 million-worth of sales from the University of Florida and to an Australian agribusiness consortium. As the firm eyes to expand the deployment of its waste conversion technology into established alternative agricultural markets, in improving global food and nutrition through biotechnology. this year may be a victorious period for the Greenbelt Resources Improving soil condition Biotechnology is also largely innovating the ways we till the soil. Through this advancement, crops are expected to give better yields, dramatically more than when sowed using traditional seeds. Also, consumers of biotechnology developed food enjoy their meals with lower levels of fertilizers. Biotechnology makes it possible for farmers to skip the heavy application of pesticides and herbicides which account for a large share in the farming cost and which some developing countries cannot afford. Today, several trials all over the world are engaged in producing a biotech seed variety that will put major crops resistant to the infestation of pests and diseases. Biotech is also known for its effectivity in increasing output of several crops with a low operating cost which translates to higher returns for farmers. Aside from this, the technology can also increase their nutritional content. This is what to be capable of. A in the 1980s showed that there may be a link between the high incidence of vitamin A deficiency in rice-eating countries — mostly in Asia — and the consumption of the staple grain. As such, Golden rice was held as the solution although the rice variety has yet to be accepted in several Asian nations. Golden Rice claims study The developer of the Golden Rice was Syngenta, one of the leading biotech agri-industry giants. The firm engages in the manufacturing and selling of seeds and agrochemicals. Syngenta is a large influence in the emergence of genetic engineering in the United Kingdom and the world. It has been expanding significantly around the globe in order to address the world’s biggest problem which is how it would feed the world’s rapidly growing population.

The impact of biotechnology on food and nutrition today

The biotechnology sector is bound to be one of the most profitable and most progressive industries in the next few decades. The volatility of an unpopular presidential administration, coupled with the release of verbal hostilities with an Asian dictatorship that can literally launch World War III, puts the global market uncertainty at a high. Yet, the biotech industry continues to attract investment. While riskier tech ventures like space tourism and cryptocurrency caution the more conservative financiers to hold on to their precious monies, the opposite goes for biotech — the more radical and revolutionary the technique or product is, the more redemptive it is hailed. That mission and vision to enhance the health and lifestyle of the people who battle each day against a blighted environment, disease, aging, and death are what propels biotechnology above the rest of the industries. As described by , technological innovations continue to harness natural elements such as human and animal cells, genomes, the soil, the wind, and water to formulate medicine and procedures that can arrest debilitating or lethal illnesses. Bio Farmers have used biotechnology to increase the yield of their crops and free their harvest of toxins and other damaging allergens. Medical research centers leverage on it to arrest the outbreak of diseases before it happens and combat life-crippling illnesses such as cancer and cellular degeneration, just to name a few. Diseases that have been previously regarded as “untreatable” can now be countered by more than 250 biotech products and services generally available to the public. The market continues to grow as more players come in. As reported by , about 670 biotech companies were thriving in the U.S., with a market capitalization of $890 billion and a yearly revenue of more than $130 billion. Statista further forecasts that biotech will surpass almost all other industries in 2017, fueled by rising concerns of both the government and the public about seemingly insoluble health problems, like medical conditions which continue to exact a heavy toll on the economy and public health alike. Examples would be cardiovascular diseases including strokes and heart attacks. The Markets Insider The biotech industry continues to grow. All these then place biotech company breakthrough products for leukemia and other severe blood diseases at the cutting-edge of the biotechnology field. It is a must-watch for investors who want to save millions of lives. Hemogenyx LLC’s (LON:HEMO) The timing and its own unique selling proposition have positioned on the radar of investors, venture capitalists, and biotech industry leaders. The biotech startup aims to revolutionize the treatment of blood diseases. In doing so, it has honed its considerable resources and teams of medical researchers and scientists into providing a breakthrough treatment for leukemia patients and others afflicted with other cancerous blood diseases. Hemogenyx Leukemia happens when cancerous white blood cells increase without restriction and, against all resistance, block the healthy distribution of blood into other parts of the body. The patient’s immune system takes a terrible blow, as they suffer a variety of medical conditions such as night sweats, nausea, fevers with chills, anemia, and constant fatigue. The uniqueness of Hemogenyx’s treatment lies in its goal of regenerating the bloodstream of the patient. First, it can be done through CDX antibodies. According to Dr. Vladislav Sandler, CEO, and founder of Hemogenyx, “The unique antibodies redirect immune cells of the patients to eliminate and attack blood stem cells of the same patient. This type of antibody will hopefully eliminate chemotherapy and radiation and solve the problem of non-specific toxicity of these treatments.” For patients needing a bone marrow or blood stem cells transplant, the second treatment uses Hu-PHEC or postnatal hemogenic endothelial cells. These cells are removed from the patient’s own liver or umbilical cord and placenta. Hemogenyx can then isolate, purify and reprogram them to become the blood stem cells that will be transplanted back to the patient. There is very little risk in the procedure as the cells are immediately compatible with the patient — after all, the patient is the donor. Incompatibility between a donated organ and the patient receiving it is one reason why bone marrow transplant, the usual treatment given to leukemia patients, fail. About 50 percent of these patients who had undergone a successful operation in this area report a breakdown or organ malfunction weeks or months after. Another obstacle to bone marrow transplant is finding a suitable donor in the first place; only 60 percent of patients on a hospital list have a good chance of securing one. Hemogenyx has gotten its own needed shot in the arm when it was acquired by investor Silver Falcon this year. According to the “reverse takeover” reached a value of £8 million. Silver Falcon issued more than 228 million shares at a value of 3.5 pence each. Silver Falcon changed its name and control at its AGM last October 4th to Hemogenyx and started trading on October 5th, under the new symbol, LON:HEMO. Digital Look, The relief that Hemogenyx could provide to more than the one million leukemia patients worldwide is a 180-degree turn from the standard medical response to an operation. If you want to have a clear idea of what it means, think of the patient’s bloodstream, once weak and dying, suddenly being rejuvenated, almost by magic, to give him power and new life.

Why this newly discovered blood-cancer treatment is at the cutting edge of biotechnology

Zika virus Source: http://www.etimesnow.com/wp-content/uploads/2016/04/Zika.jpg I am exceptionally pleased and excited to share this short work update. We have finalised and are currently testing dSPP — . Our resource, currently under peer-review, will facilitate the access to ready protein data for , including protein involved in Zika virus, HIV, Alzheimer’s, Parkinson’s, p53 mutants, human prion proteins, and many others. the first protein machine learning database machine learning 7000+ high value medical targets We are beta-testing user interface and UX. I attach an example for Zika virus NS3 protease fragment search. Please note the Machine learning section, and various interactive data representations for and . Keras Google’s Tensorflow Useful post? If so, make my day by clicking the heart below! About the Author is the founder and the architect of . You can connect with him on , , , and . Kamil Tamiola Peptone — The Protein Intelligence Company AngelList LinkedIn Twitter Researchgate

Keras and Tensorflow meet protein biotechnology — testing dSPP for public release

Metamorphosis Commenced: Network States v0.01

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AI in Biotech: Challenges, Use Cases and Prospects

“Jurassic Park” may not be as far-fetched as it seems. Scientists have been trying to find ways to bring extinct species back to life for some time now, and AI could finally make it happen. While some regulators call AI an extinction-level threat, the opposite may also be true. It could reverse extinction — perhaps not for dinosaurs, but feasibly for species like the woolly mammoth. Doing so could also play an important role in the fight against climate change. How De-Extinction Works De-extinction is the culmination of many cutting-edge technologies. It starts with gene-editing technologies like CRISPR, and AI helps throughout the entire process. Here’s a closer look at how it works. Genome Sequencing The first step in de-extinction is to collect the DNA of an extinct animal — like the woolly mammoth — and a close living relative — like the Asian elephant. While usable dinosaur DNA samples may be long gone, the mammoth’s relatively recent extinction and cold habitat mean it still has well-preserved genes. Once scientists have gathered this DNA, they must sequence each species’ genome. This process uncovers the order of each gene’s building blocks to learn how they work and what characteristics they produce. It’s difficult and time-consuming work, so it’s an ideal use case for AI. Studies show that AI shortens the time spent in genome sequencing and reduces errors in the process. Speed and accuracy are big concerns here, so AI is now essential in this stage of de-extinction. Filling in the Gaps After sequencing both species’ genomes, scientists compare them to see what elephant genes they must change to resemble the woolly mammoth’s. AI is crucial in this step, as there are gaps left to fill after sequencing. DNA has a 521-year half-life, so even well-preserved samples from over 1,000 years ago aren’t complete. AI can analyze genes to predict the order of the missing bits. It can then compare them to those of the Asian elephant to determine what elephant genes it can keep and what it must modify to look more like a mammoth. Machine learning’s predictive capabilities make it the perfect tool for this job. Accurately predicting what customers want is how AI saves Netflix $1 billion annually, and finding similarities in DNA sequences is a similar task. Gene Insertion and Verification It’s now time to modify Asian elephant genes to essentially create complete woolly mammoth DNA. This process is eerily similar to how it works in “Jurassic Park,” at least in the basics. Like in Michael Crichton’s work, real-life scientists cut out bits of living species’ DNA that don’t match and insert genes from the extinct species. This is possible through a technology called CRISPR gene editing — the same innovation that helps fight diseases like sickle cell anemia and malaria. After inserting mammoth genes into elephant DNA, scientists must verify that the resulting cells possess mammoth traits. Once again, AI is the ideal solution. Machine learning can test these cells faster and more accurately than manual methods. Embryo Transfer, Growth, and Birth At this point, scientists will have created hybrid elephant-mammoth cells. They remove the nucleus from an Asian elephant egg cell and replace it with the hybrid mammoth nucleus. They then stimulate the egg so it fertilizes and grows into an embryo. Once they have a healthy embryo, scientists transfer it to an African elephant to carry to term. African elephants are larger and have the longest pregnancy of any mammal, so they’re ideal mothers to grow a baby mammoth. After roughly 22 months, the elephant will give birth to the hybrid mammoth. While the mammoth’s genes won’t be identical to its extinct ancestors, it’ll essentially be a real woolly mammoth brought back from extinction. Ongoing De-Extinction Attempts Several research organizations are following this process to de-extinct species like the woolly mammoth. One biotechnology company — Colossal Laboratories — aims to resurrect the woolly mammoth by 2027 and is currently building the necessary genetic libraries to create the hybrid DNA. Colossal also hopes to de-extinct species like the dodo and Tasmanian tiger. While no project has successfully cloned an extinct species that lived more than a few minutes, advances in AI and gene editing technology are bringing the possibility closer. Other researchers are focusing on critically endangered species — not quite extinct but about to be. Scientists have successfully cloned a black-footed ferret using decades-old DNA, showing it’s possible to de-extinct animals with old genes. Researchers at the San Diego Zoo Alliance are trying to do the same for the northern white rhino, just two of which exist today. Why It Matters As cool as it is, why would scientists bother de-extincting species? It’s an expensive, complicated process, so what’s the point? Unlike in “Jurassic Park,” there is a noble goal here. Bringing extinct or critically endangered species back could help protect the planet. Woolly mammoths could help fight climate change, as these animals clear dead or invasive tree species to restore grasslands. Bringing more recently extinct animals back to life would restore a full, healthy ecosystem in some areas to protect other species. In cases like the white rhino, it would right the wrongs of humanity’s past by reversing forced extinction. If nothing else, successful de-extinction would be a big step forward for AI in genetic engineering. It would prove this technology’s potential to fight seemingly impossible odds. Scientists already believe AI-powered gene editing could improve global health and combat climate change, so any advances in the field are worth noticing. Ethical Complications Despite this vast potential, AI-powered de-extinction has some controversy. Some argue that bringing species like the woolly mammoth into a warmer, harsher climate, which they’re not well-adapted to, may be cruel to these animals. There’s also the argument that the money and time spent on this research could go to other, more immediate climate and health issues. Some also have fears about AI gene editing going too far. Successful de-extinction could snowball into issues of people genetically modifying humans to have unique abilities or creating dangerous genetic weapons. Many of these fears are theoretical but deserve attention as this field advances. AI Could Bring Species Back From the Dead While there are still some ethical and technological complications, de-extinction shows promise. It would be a major step forward for biotechnology if these projects work out, and AI will likely be the difference-maker. AI has plenty of ethical and environmental concerns. However, it’s hard to deny its potential for protecting the natural world. Using it for conservation efforts could ensure the world benefits more from this technology than it suffers. “Jurassic Park” may not be as far-fetched as it seems. Scientists have been trying to find ways to bring extinct species back to life for some time now, and AI could finally make it happen. While some regulators call AI an extinction-level threat , the opposite may also be true. It could reverse extinction — perhaps not for dinosaurs, but feasibly for species like the woolly mammoth. Doing so could also play an important role in the fight against climate change. call AI an extinction-level threat call AI an extinction-level threat How De-Extinction Works De-extinction is the culmination of many cutting-edge technologies. It starts with gene-editing technologies like CRISPR, and AI helps throughout the entire process. Here’s a closer look at how it works. Genome Sequencing The first step in de-extinction is to collect the DNA of an extinct animal — like the woolly mammoth — and a close living relative — like the Asian elephant. While usable dinosaur DNA samples may be long gone, the mammoth’s relatively recent extinction and cold habitat mean it still has well-preserved genes. Once scientists have gathered this DNA, they must sequence each species’ genome. This process uncovers the order of each gene’s building blocks to learn how they work and what characteristics they produce. It’s difficult and time-consuming work, so it’s an ideal use case for AI. Studies show that AI shortens the time spent in genome sequencing and reduces errors in the process. Speed and accuracy are big concerns here, so AI is now essential in this stage of de-extinction. shortens the time spent in genome sequencing shortens the time spent in genome sequencing Filling in the Gaps After sequencing both species’ genomes, scientists compare them to see what elephant genes they must change to resemble the woolly mammoth’s. AI is crucial in this step, as there are gaps left to fill after sequencing. DNA has a 521-year half-life , so even well-preserved samples from over 1,000 years ago aren’t complete. has a 521-year half-life has a 521-year half-life AI can analyze genes to predict the order of the missing bits. It can then compare them to those of the Asian elephant to determine what elephant genes it can keep and what it must modify to look more like a mammoth. Machine learning’s predictive capabilities make it the perfect tool for this job. Accurately predicting what customers want is how AI saves Netflix $1 billion annually , and finding similarities in DNA sequences is a similar task. saves Netflix $1 billion annually saves Netflix $1 billion annually Gene Insertion and Verification It’s now time to modify Asian elephant genes to essentially create complete woolly mammoth DNA. This process is eerily similar to how it works in “Jurassic Park,” at least in the basics. Like in Michael Crichton’s work, real-life scientists cut out bits of living species’ DNA that don’t match and insert genes from the extinct species. This is possible through a technology called CRISPR gene editing — the same innovation that helps fight diseases like sickle cell anemia and malaria. After inserting mammoth genes into elephant DNA, scientists must verify that the resulting cells possess mammoth traits. Once again, AI is the ideal solution. Machine learning can test these cells faster and more accurately than manual methods. Embryo Transfer, Growth, and Birth At this point, scientists will have created hybrid elephant-mammoth cells. They remove the nucleus from an Asian elephant egg cell and replace it with the hybrid mammoth nucleus. They then stimulate the egg so it fertilizes and grows into an embryo. Once they have a healthy embryo, scientists transfer it to an African elephant to carry to term. African elephants are larger and have the longest pregnancy of any mammal , so they’re ideal mothers to grow a baby mammoth. the longest pregnancy of any mammal the longest pregnancy of any mammal After roughly 22 months, the elephant will give birth to the hybrid mammoth. While the mammoth’s genes won’t be identical to its extinct ancestors, it’ll essentially be a real woolly mammoth brought back from extinction. Ongoing De-Extinction Attempts Several research organizations are following this process to de-extinct species like the woolly mammoth. One biotechnology company — Colossal Laboratories — aims to resurrect the woolly mammoth by 2027 and is currently building the necessary genetic libraries to create the hybrid DNA. resurrect the woolly mammoth by 2027 resurrect the woolly mammoth by 2027 Colossal also hopes to de-extinct species like the dodo and Tasmanian tiger. While no project has successfully cloned an extinct species that lived more than a few minutes, advances in AI and gene editing technology are bringing the possibility closer. Other researchers are focusing on critically endangered species — not quite extinct but about to be. Scientists have successfully cloned a black-footed ferret using decades-old DNA, showing it’s possible to de-extinct animals with old genes. Researchers at the San Diego Zoo Alliance are trying to do the same for the northern white rhino, just two of which exist today. successfully cloned a black-footed ferret successfully cloned a black-footed ferret Why It Matters As cool as it is, why would scientists bother de-extincting species? It’s an expensive, complicated process, so what’s the point? Unlike in “Jurassic Park,” there is a noble goal here. Bringing extinct or critically endangered species back could help protect the planet. Woolly mammoths could help fight climate change, as these animals clear dead or invasive tree species to restore grasslands. Bringing more recently extinct animals back to life would restore a full, healthy ecosystem in some areas to protect other species. In cases like the white rhino, it would right the wrongs of humanity’s past by reversing forced extinction. If nothing else, successful de-extinction would be a big step forward for AI in genetic engineering. It would prove this technology’s potential to fight seemingly impossible odds. Scientists already believe AI-powered gene editing could improve global health and combat climate change, so any advances in the field are worth noticing. could improve global health could improve global health Ethical Complications Despite this vast potential, AI-powered de-extinction has some controversy. Some argue that bringing species like the woolly mammoth into a warmer, harsher climate, which they’re not well-adapted to, may be cruel to these animals. There’s also the argument that the money and time spent on this research could go to other, more immediate climate and health issues. Some also have fears about AI gene editing going too far. Successful de-extinction could snowball into issues of people genetically modifying humans to have unique abilities or creating dangerous genetic weapons. Many of these fears are theoretical but deserve attention as this field advances. AI Could Bring Species Back From the Dead While there are still some ethical and technological complications, de-extinction shows promise. It would be a major step forward for biotechnology if these projects work out, and AI will likely be the difference-maker. AI has plenty of ethical and environmental concerns. However, it’s hard to deny its potential for protecting the natural world. Using it for conservation efforts could ensure the world benefits more from this technology than it suffers.

The Role of AI in Resurrecting Extinct Species

বিলুপ্ত প্রজাতির পুনরুত্থানে এআই-এর ভূমিকা

Die Rolle der KI bei der Wiederbelebung ausgestorbener Arten

El papel de la IA en la resurrección de especies extintas

Le rôle de l’IA dans la résurrection des espèces disparues

विलुप्त प्रजातियों को पुनर्जीवित करने में एआई की भूमिका

絶滅した種の復活におけるAIの役割

멸종된 종을 부활시키는 데 있어 AI의 역할

O papel da IA na ressurreição de espécies extintas

Роль ИИ в воскрешении вымерших видов

Soyu Tükenmiş Türlerin Diriltilmesinde Yapay Zekanın Rolü

Vai trò của AI trong việc hồi sinh các loài đã tuyệt chủng

人工智能在复活灭绝物种中的作用

At SXSW this year, , CEO of the Future Today Institute, once again delivered a session as a lighthouse in the "technology supercycle" reshaping our world. Webb, a renowned author and professor at NYU Stern School of Business, shared key insights from the in an enlightening one-hour session. Despite having to catch a rerun due to simultaneous sessions, here's what I gathered: Amy Webb 17th Annual Technology Trends Report The Technology Supercycle We're smack in the middle of a "technology supercycle era," driven by the convergence of three general-purpose technologies: Artificial Intelligence (AI) Biotechnology Connected Device/Sensor Ecosystem This supercycle has the potential to reshape our economy and society in ways unseen since the Industrial Revolution and the dawn of the internet age. AI Trends Despite the hype and popularity of AI, there are still unresolved and often misunderstood big issues, including bias, accountability, and the risk of open-source models being used for nefarious purposes. Generative AI is evolving rapidly, moving from text-based models to a "concept to concrete" paradigm that can embody broad ideas. Smart Device Ecosystem: A New Black Mirror Episode There's an explosion of interest and development in smart device and sensor technology. These tech products, which include "face computers" (VR/AR headsets) and wearables that can read human intention, feed more real-world data into AI through "large action models." This raises privacy and social scoring concerns. Biotechnology Breakthroughs Advances in synthetic biology and biological computers made from human brain cells (organoid intelligence) could move us beyond silicon-based computing. This could pave the way for faster, more efficient, and more powerful computing systems that require less energy. This aligns with the theory of exascale computers mentioned in the MIT Technology Trends Report. Societal Impacts and Recommendations The concentration of power among a group of tech leaders following a techno-utopian vision is concerning. Governments should establish new departments and organizations to plan for the disruptive effects of the technology supercycle on industries and jobs. Companies must start mapping out evolving value networks to anticipate disruptions and create future value. To Succeed Individually in the Technology Supercycle, Webb Suggests: Strive to be informed about trends shaping our era and their potential impacts on your business. Begin to adopt strategic foresight and long-term planning to anticipate and adapt to disruptive changes. Engage in discussions on shaping the technology supercycle towards a more equitable future for all, and take an active role. This session with Amy Webb offered a comprehensive roadmap for navigating the currents and undercurrents of the technology supercycle, emphasizing the importance of proactive engagement and strategic planning to thrive in the rapidly evolving digital landscape.

What Is the Technology Supercycle?

Using pgvector To Locate Similarities In Enterprise Data

এন্টারপ্রাইজ ডেটাতে মিল খুঁজে পেতে pgvector ব্যবহার করা

Verwenden von pgvector zum Auffinden von Ähnlichkeiten in Unternehmensdaten

Uso de pgvector para localizar similitudes en datos empresariales

Utilisation de pgvector pour localiser les similitudes dans les données d'entreprise

एंटरप्राइज़ डेटा में समानताएँ खोजने के लिए pgvector का उपयोग करना

pgvector を使用して企業データ内の類似点を特定する

pgVector를 사용하여 기업 데이터의 유사점 찾기

Usando pgvector para localizar semelhanças em dados corporativos

Использование pgvector для поиска сходств в корпоративных данных

Kurumsal Verilerdeki Benzerlikleri Bulmak İçin pgvector'u Kullanma

Sử dụng pgvector để xác định điểm tương đồng trong dữ liệu doanh nghiệp

使用 pgvector 查找企业数据中的相似之处

This paper is available on arxiv under CC 4.0 license. Authors: (1) Jeffrey Ouyang-Zhang, UT Austin (2) Daniel J. Diaz, UT Austin (3) Adam R. Klivans, UT Austin (4) Philipp Krähenbühl, UT Austin Table of Links Abstract & Introduction Related Works Preliminary Methodology Results Limitations Conclusion, Acknowledgements, & References Experimental Setting & Additional Results 7 Conclusion We present a method that efficiently scales thermodynamic stability prediction from single mutations to higher-order mutations. Our key insight is that the effects of mutations on the same protein are correlated. Thus, for a target protein, it suffices to run a deep backbone once and decode the effect of all mutations simultaneously using a shallow decoder. With the AlphaFold model as our backbone, our method outperforms existing methods on a variety of single and multiple mutation benchmarks. 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Predicting a Protein’s Stability
under a Million Mutations: Conclusion, Acknowledgement & References

These Biotech Execs Made Perfectly Timed Trades in Health Care Stocks 

এই বায়োটেক এক্সিক্স স্বাস্থ্যসেবা স্টকগুলিতে নিখুঁতভাবে সময়োপযোগী ট্রেড করেছেন

Diese Biotech-Manager haben zum perfekten Zeitpunkt Geschäfte mit Gesundheitsaktien getätigt

Estos ejecutivos de biotecnología realizaron operaciones en el momento perfecto en acciones de atención médica

Ces dirigeants de la biotechnologie ont effectué des transactions parfaitement synchronisées sur les actions du secteur de la santé

इन बायोटेक अधिकारियों ने स्वास्थ्य देखभाल शेयरों में बिल्कुल सही समय पर व्यापार किया

これらのバイオテクノロジー幹部はヘルスケア株で完璧なタイミングで取引を行った

헬스케어 주식에서 완벽한 타이밍에 거래한 생명공학 경영진

Esses executivos de biotecnologia fizeram negociações perfeitamente cronometradas em ações de saúde

Эти руководители биотехнологий совершили идеально своевременные сделки по акциям здравоохранения

Bu Biyoteknoloji Yöneticileri Sağlık Hisse Senetlerinde Mükemmel Zamanlanmış Ticaret Yaptı

Những nhà điều hành công nghệ sinh học này đã thực hiện giao dịch theo thời gian hoàn hảo đối với cổ phiếu chăm sóc sức khỏe

这些生物技术高管在医疗保健股上进行了完美的时机交易

Authors: (1) JunJie Wee, Department of Mathematics, Michigan State University; (2) Jiahui Chen, Department of Mathematical Sciences, University of Arkansas; (3) Kelin Xia, Division of Mathematical Sciences, School of Physical and Mathematical Sciences Nanyang Technological University & xiakelin@ntu.edu.sg; (4)Guo-Wei Wei, Department of Mathematics, Michigan State University, Department of Biochemistry and Molecular Biology, Michigan State University, Department of Electrical and Computer Engineering, Michigan State University & xiakelin@ntu.edu.sg. Table of Links Abstract & Introduction Results Discussion Conclusion Materials and Methods Software and resources, Code and Data Availability Supporting Information, Acknowledgments & References Supporting Information Supporting Information is available for supplementary tables, figures, and methods. Acknowledgments This work was supported in part by NIH grants R01GM126189, R01AI164266, and R01AI146210, NSF grants DMS-2052983, DMS-1761320, and IIS-1900473, NASA grant 80NSSC21M0023, MSU Foundation, Bristol-Myers Squibb 65109, and Pfizer. It was supported in part by Nanyang Technological University Startup Grant M4081842.110, Singapore Ministry of Education Academic Research fund Tier 1 RG109/19 and Tier 2 MOE-T2EP20120-0013, MOE-T2EP20220- 0010, and MOE-T2EP20221-0003. References [1] Y. Qiu and G.-W. Wei, “Persistent spectral theory-guided protein engineering,” Nature Computational Science, vol. 3, no. 2, pp. 149–163, 2023. [2] R. Guerois, J. E. Nielsen, and L. Serrano, “Predicting changes in the stability of proteins and protein complexes: a study of more than 1000 mutations,” Journal of molecular biology, vol. 320, no. 2, pp. 369–387, 2002. [3] P. Sormanni, F. A. Aprile, and M. Vendruscolo, “The CamSol method of rational design of protein mutants with enhanced solubility,” Journal of molecular biology, vol. 427, no. 2, pp. 478–490, 2015. [4] Y. Tian, C. Deutsch, and B. Krishnamoorthy, “Scoring function to predict solubility mutagenesis,” Algorithms for Molecular Biology, vol. 5, no. 1, pp. 1–11, 2010. [5] Y. Yang, A. Niroula, B. Shen, and M. Vihinen, “PON-Sol: Prediction of effects of amino acid substitutions on protein solubility,” Bioinformatics, vol. 32, no. 13, pp. 2032–2034, 2016. [6] L. Paladin, D. Piovesan, and S. C. Tosatto, “SODA: Prediction of protein solubility from disorder and aggregation propensity,” Nucleic acids research, vol. 45, no. W1, pp. W236– W240, 2017. [7] J. Van Durme, G. De Baets, R. Van Der Kant, M. Ramakers, A. Ganesan, H. Wilkinson, R. Gallardo, F. Rousseau, and J. Schymkowitz, “Solubis: a webserver to reduce protein aggregation through mutation,” Protein Engineering, Design and Selection, vol. 29, no. 8, pp. 285–289, 2016. 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Contributing Partners: NIH, NSF, NASA, and More Back TopLapGBT's Advancements

Authors: (1) JunJie Wee, Department of Mathematics, Michigan State University; (2) Jiahui Chen, Department of Mathematical Sciences, University of Arkansas; (3) Kelin Xia, Division of Mathematical Sciences, School of Physical and Mathematical Sciences Nanyang Technological University & xiakelin@ntu.edu.sg; (4)Guo-Wei Wei, 1Department of Mathematics, Michigan State University, Department of Biochemistry and Molecular Biology, Michigan State University, Department of Electrical and Computer Engineering, Michigan State University & xiakelin@ntu.edu.sg. Table of Links Abstract & Introduction Results Discussion Conclusion Materials and Methods Software and resources, Code and Data Availability Supporting Information, Acknowledgments & References Abstract Protein mutations can significantly influence protein solubility, which results in altered protein functions and leads to various diseases. Despite of tremendous effort, machine learning prediction of protein solubility changes upon mutation remains a challenging task as indicated by the poor scores of normalized Correct Prediction Ratio (CPR). Part of the challenge stems from the fact that there is no three-dimensional (3D) structures for the wild-type and mutant proteins. This work integrates persistent Laplacians and pre-trained Transformer for the task. The Transformer, pretrained with hunderds of millions of protein sequences, embeds wild-type and mutant sequences, while persistent Laplacians track the topological invariant change and homotopic shape evolution induced by mutations in 3D protein structures, which are rendered from AlphaFold2. The resulting machine learning model was trained on an extensive data set labeled with three solubility types. Our model outperforms all existing predictive methods and improves the state-of-the-art up to 15% Mutation, Protein solubility, Persistent Laplacian, Transformer, AlphaFold2. Keywords: 1 Introduction Genetic mutations alter the genome sequence, leading to changes in the corresponding amino acid sequence of a protein. These alternations have far-reaching implications on the protein’s structure, function, and stability, affecting attributes such as folding stability, binding affinity, and solubility. The consequences of protein mutations have been extensively studied in diverse fields such as evolutionary biology, cancer biology, immunology, directed evolution, and protein engineering [1]. Understanding the impact of genetic mutations on protein solubility is crucial in various fields, including protein engineering, drug discovery, and biotechnology. Accurately analyzing and predicting the impact of mutations on protein solubility is therefore crucial in many fields, facilitating the engineering of proteins with desirable functions. There are numerous intricately interconnected factors impacting protein solubility, ranging from amino acid sequence arrangement, post-translational modifications, protein-protein interactions, to environmental conditions, such as solvent type, ion type and concentration, the presence of small molecules, temperature, etc. Unfortunately, the existing data set does not contain sufficient information. This complexity poses significant challenges for the accurate prediction and modeling of protein solubility, often requiring multifaceted computational approaches for reliable outcomes. Computational predictions serve as a valuable complement to experimental mutagenesis analysis of protein stability changes upon mutation. Such computational approaches offer several advantages, including being economical, efficient, and provide a viable alternative to laborintensive site-directed mutagenesis experiments [2]. As a result, the development of accurate and reliable computational techniques for mutational impact prediction could substantially enhance the throughput and accessibility of research in protein engineering and drug discovery Over the years, a variety of computational methods have been developed to explore the effects of mutations on protein solubility, including but not limited to CamSol [3], OptSolMut [4], PON-Sol [5], SODA [6], Solubis [7], and others as summarized in a recent review [8]. CamSol employs an algorithm to construct a residue-specific solubility profile, although no explicit method has been made publicly available. OptSolMut is trained on 137 samples, each featuring single or multiple mutations affecting solubility or aggregation. PON-Sol utilizes a random forest model trained on a dataset of 406 single amino acid substitutions labeled as solubilityincreasing, solubility-decreasing, or exhibiting no change in solubility. SODA, which is based on the PON-Sol data, specifically targets samples with decreasing solubility [6]. Solubis is an optimization tool that increases protein solubility and integrates interaction analysis from FoldX [2], aggregation prediction from TANGO [9], and structural analysis from YASARA [10]. Recently, PON-Sol2 [11] extended the original PON-Sol dataset and employed a gradient boosting algorithm for sequence-based predictions. Despite of intensive effort, the current prediction accuracy in terms of normalized Correct Prediction Ratio (CPR) remains very low, calling for innovative strategies. Topological data analysis (TDA) is a relatively new approach for data science. Its main technique is persistent homology [12, 13]. The essential idea of persistent homology is to construct a multiscale analysis of data in terms of topological invariants. The resulting changes of topological invariants over scales can be used to characterize the intricate structures of data, leading to an unusually powerful approach in describing protein structure, flexibility, and folding [14]. Persistent homology was integrated with machine learning for the classification of proteins in 2015 [15], which was one the first integrations of TDA and machine learning, and the predictions of mutation-induced protein stability changes [16, 17] and protein-protein binding free energy changes [18, 19]. One of the major achievements of TDA is its winning of D3R Grand Challenges, an annual worldwide competition series in computer-aided drug design [20, 21]. A nearly comprehensive summary of the early success of TDA in biological science was given in a review [22]. However, persistent homology only tracks the changes in topological invariants and cannot capture homotopic shape evolution of data over scales or induced by mutations. To overcome this limitation, Wei and coworkers introduced persistent combinatorial Laplacians, also called persistent spectral graphs, on point clouds [23] and evolutionary de Rham-Hodge method on manifolds [24] in 2019. The essence of these methods is the persistent topological Laplacians (PTLs) either on point clouds or on manifolds. PTLs not only fully capture the topological invariants in its harmonic spectra as those given by persistent homology, but also capture the homotopic shape evolution of data during the multiscale analysis or a mutation process. PTLs were applied to the predictions of protein flexibility [25] and protein-ligand binding free energies [26], protein–protein interactions[27, 28], and protein engineering [1]. The most remarkable accomplishment by persistent Laplacian is its accurate forecasting of emerging dominant SARS-CoV-2 variants BA.4 and BA.5 about two months in advance [29]. However, TDA approaches depend on the biomolcular structures, which may not be available. In fact, many proteins involved in the present study do not have 3D structures. In recent years, advanced natural language processing (NLP) models, including Transformers and long short-term memory (LSTM), have been widely implemented across various domains to extract protein sequence information. For example, Tasks Assessing Protein Embedding (TAPE) introduced three different architectures, namely transformer, dilated residual network (ResNet), and LSTM [30]. Additionally, LSTM-based models like Bepler [31] and UniRep [32] have been developed. Additionally, large-scale protein transformer models trained on extensive datasets comprising hundreds of millions of sequences have made significant advancements in the field. These models, including Evolutionary Scale Modeling (ESM) [33] and ProtTrans [34, 35], have exhibited exceptional performance in capturing a variety of protein properties. ESM, for instance, allows for fine-tuning based on either downstream task data or local multiple sequence alignments [36]. In the present work, we leverage the pre-trained ESM transformer model to extract crucial information from protein sequences. In this work, we will integrate transformer-based sequence embedding and persistent topological Laplacians to predict protein solubility changes upon mutation. While sequence-based models can be applied without 3D structural information, the PTL-based features require highquality structures. We generate 3D structures of wild type proteins from AlphaFold2 [37] to facilitate topological embedding. By combining both embedding approaches, they naturally complement each other in classifying protein solubility changes upon mutation. These embeddings are fed into an ensemble classifier, gradient boosted trees (GBT), to build a machine learning model, called TopLapGBT. We validate TopLapGBT on the classification of protein solubility changes upon mutation. We demonstrate that this integrated machine learning model gives rise to a substantial improvement as compared to existing state-of-the-art models. Residue-Similarity plots are also applied to assess how well the TopLapGBT model classify three solubility labels. This paper is under CC 4.0 license. available on arxiv

Persistent Laplacian and Pre-Trained Transformer for Protein Solubility Changes Upon Mutation

On the occasion of Singaporean Deputy Prime Minister Lawrence Wong’s visit to Washington, D.C., the United States and Singapore launched the U.S.-Singapore Critical and Emerging Technology (CET) Dialogue.  National Security Advisor Jake Sullivan, Acting Special Envoy for Critical and Emerging Technology Seth Center (on behalf of Secretary of State Antony Blinken), Minister for Foreign Affairs Dr. Vivian Balakrishnan, and Minister for Communications and Information and Minister-in-Charge of Smart Nation and Cybersecurity Josephine Teo led the inaugural U.S. Singapore CET Dialogue, with opening remarks by Deputy Prime Minister Wong. They were joined on the U.S. side by the Deputy Secretary of Commerce, the Deputy Secretary of Energy, the Director of the National Science Foundation (NSF), the Director of the National Institute of Standards and Technology (NIST), the Deputy National Security Advisor for International Economics, and senior officials from the U.S. Department of State, Department of Commerce, Department of Energy, United States Trade Representative, Department of Defense, and National Security Council.  On the Singaporean side, Minister of State for Trade & Industry Alvin Tan, senior officials from the Ministry of Communications and Information, Ministry for Trade and Industry, the Ministry of Defense, the Ministry of Foreign Affairs, and the Chairman of the Economic Development Board and the Chief Executive of the Infocomm Media Development Authority participated. The two sides discussed opportunities to bolster research, innovation, and commercial ties to expand the frontiers of scientific knowledge, promote prosperity, and deliver public goods to the Indo-Pacific region, especially ASEAN partners.  The United States and Singapore also discussed economic security and technology protection measures to manage risks to national security while abiding by our long-standing commitment to open investment.  The high-level discussions were followed by a dialogue with industry hosted by the U.S. Chamber of Commerce focused on AI innovation and safety and co-chaired by U.S. Deputy Secretary of Commerce Don Graves and Singapore Minister of Communications and Information Teo. To expand and deepen our technology partnership, the United States and Singapore committed to launch new bilateral initiatives and welcomed enhanced cooperation between our governments, industry, and academia across the following domains: Artificial Intelligence (AI) Welcomed the completion of a mapping exercise between the U.S. Department of Commerce’s National Institute of Standards and Technology (NIST) AI Risk Management Framework and the Singapore Infocomm Media Development Authority’s AI Verify Establishing a bilateral AI Governance Working Group focused on advancing shared principles for safe, trustworthy, and responsible AI innovation, to complement the United States’ Voluntary AI Commitments and a potential multilateral AI Code of Conduct. Expanding collaboration between the U.S. National Science Foundation and AI Singapore (AISG) through joint research and educational funding opportunities focused on trustworthy and safe AI systems. Exploring reciprocal certification programs for American and Singaporean AI professionals on the basis of shared standards, tests, and benchmarks. Digital Economy Developing a Roadmap for Digital Economic Cooperation that charts common principles and objectives on priority issues such as data governance, digital standards, digital inclusion, consumer protection, and ensuring small- and medium-enterprises can benefit from opportunities in the digital economy. Exploring opportunities to strengthen bilateral collaboration on digital payments, including to shape international best practices. Collaborating to facilitate trusted data flows with effective privacy protections, including through work under the U.S.-Singapore Partnership for Growth and Innovation (PGI) and through supporting the expansion of the Global Cross-Border Privacy Rules Forum. Biotechnology Convening U.S. and Singapore universities, research institutions, private sector, and science agencies to advance shared research and development (R&D) priorities for biotechnology; talent exchanges; and sharing of best practices for startups around commercialization, scaling, and R&D translation efforts. Exploring opportunities for R&D collaboration in synthetic biology, cell and gene therapeutics, viral and viral delivery systems. Climate and Resilient Critical Infrastructure Upgrading long-standing collaboration on smart cities, with a focus on climate resilience, under the auspices of the U.S.-ASEAN Smart Cities Partnership. Working to establish a Smart Cities Program on AI through the U.S.-Singapore Third Country Training Program to deliver capacity-building to ASEAN and Pacific Islands Forum states. Supporting regional efforts to decarbonize and deploy renewable energy, including through ongoing research efforts through the U.S.-Singapore Climate Partnership. Collaborating on standards, rules, and norms for promoting the protection, maintenance, and streamlined processes for subsea cables, including at international platforms such as the International Cable Protection Committee. Quantum Information Science and Technology Expanding government, academic, and private sector exchanges through the State Department International Visitor Leadership Program and other potential longer-term programs including between university partners. Deepening information-sharing on Post Quantum Cryptography migration between the U.S. Department of Commerce’s National Institute of Standards and Technology and the Department of Homeland Security and Singapore’s National Quantum Office and Ministry of Communications and Information. Defense Innovation Concluding a Memorandum of Understanding between the U.S. Department of Defense’s Defense Innovation Unit and the Singapore Ministry of Defence to more deeply integrate our bilateral defense innovation ecosystems, in support of stability and security in the Indo-Pacific and beyond. The United States and Singapore look forward to institutionalizing the CET Dialogue as a mechanism to accelerate collaboration—both bilaterally and with like-minded partners—and pursue ambitious objectives for our technology partnership in service of our shared vision for a secure, peaceful, stable, and prosperous Indo-Pacific region. This content was originally published in October 12, 2023, on whitehouse.gov.

Key Takeaways from the Inaugural US-Singapore CET Dialogue 

What’s to become of these ‘supersoldiers’ once their service has ended? Cyborgs and genetically enhanced “supersoldiers” are projected to be the , according to a recent RAND Corporation report. warfighters of the future Published on January 2, 2024, the , “ ,” highlights advances in human-machine systems, along with AI and synthetic biology as being among the technologies that will be used to engineer the future warfighter. report Plagues, Cyborgs, and Supersoldiers: The Human Domain of War According to the report, these technologies will give rise to seemingly where soldiers will be able to control machines using their thoughts, along with the ability to genetically modify warfighters, so that they will be able to survive in “the harshest of combat environments.” telepathic capabilities “Given the rapid advancements brought about by the 21st-century biotechnology revolution, the application of artificial intelligence (AI) algorithms, and advanced human-machine systems, we see a complex, high-threat landscape emerging where future wars are fought with humans controlling hyper-sophisticated machines with their thoughts; the military-industrial base is disturbed by synthetically generated, genomically targeted plagues; and the future warfighter goes beyond the baseline genome to become an enhanced warfighter who is capable of survival in the harshest of combat environments” The (IoB), which refers to an ecosystem consisting of interconnected devices that can be worn, ingested, or implanted, is one way in which warfighters of the future are projected to become cyborgs. Internet of Bodies The authors note that “ .” IoB and related technologies present a variety of potential opportunities to warfighters. For example, the US Army is running studies to determine whether wearables can help with soldier wellbeing and fitness. Australian researchers have shown that military robot quadrupeds can be steered by brain signals collected and translated by a graphene sensor worn behind the ear of a nearby soldier On the positive side, “Combining IoB data with advanced machine learning (ML) and AI algorithms can potentially enable tremendous advancements in health care, particularly precision medicine.” However, the IoB also comes with grave risks in terms of , intelligence gathering, privacy, and targeted attacks that can essentially hijack the brain of the user and cause unimaginable harm. cybersecurity As (BCIs) become more prevalent, the report warns: brain-computer interfaces “If this technology were hacked, a malicious adversary could potentially inject fear, confusion, or anger into the commander’s brain and cause them to make decisions that result in serious harm” The authors go on to explain that this type of brain hacking is already considered a threat and that “ .” several organizations based in China were found to ‘use biotechnology processes to support Chinese military end uses and end users, to include purported brain-control weaponry’ and, because of this, these entities were added to the Department of Commerce’s Entity List to restrict trade with those organizations While brain hacking is discussed in the context of military environments, the same technology is increasingly becoming more commercially available for the general public, including the workplace. For example, speaking at the World Economic Forum (WEF) annual meeting in January 2023, Dr. Nita Farahany from Duke University explained: “We can pick up and decode faces that you’re seeing in your mind — simple shapes, numbers, your PIN number to your bank account” https://twitter.com/TimHinchliffe/status/1616114732536303619?embedable=true “Artificial intelligence has enabled advances in decoding brain activity in ways we never before thought possible,” said Farahany. “What you think, what you feel — it’s all just data — data that in large patterns can be decoded using artificial intelligence,” she added. And the devices to decode the human brain don’t have to be as invasive as a brain implant. The devices can be as non-invasive as a “Fitbit for your brain.” https://twitter.com/TimHinchliffe/status/1616107080259100672?embedable=true Another type of IoB risk, according to the recent RAND report, “ .” derives from information security issues with IoB-collected data For example, “A security vulnerability in the Strava app reportedly allowed unknown users to identify and track the movements of Israeli service members inside military bases, even if users limited who could view their Strava profiles,” and “In 2023, it was reported that the Strava app might have been used to track a Russian submarine commander who was killed while jogging.” In a similar vein, US Intelligence Advanced Research Projects Activity (IARPA) director Catherine Marsh said back in 2021 that the as “a growing source of data that can be collected to learn intent.” US spy community was increasingly looking to Internet of Things (IoT) devices “ ,” said Marsh. Developing these new sensors and detectors, as well as thinking about clever ways to collect multi-modal data to reveal what our adversaries are attempting to hide from us is at the very core of what our collection programs are aimed at doing Moving beyond the IoB and cyborgs, another way in which the warfighter of the future is projected to become a “supersoldier” is through genetic engineering, specifically genomic enhancement. According to the recent RAND report, genomic enhancement refers to “ .” the process of isolating and using accessible genomic information or treatments to alter a trait in the human body or the environment to enhance resiliency at a micro (individual) or macro (societal) scale The authors predict that “ .” potential near-future genomic enhancements of key warfighting traits could be the ability to function with less sleep, more physical stamina, and improved breathing capacity This recent report echoes another RAND entitled, “ ,” which outlined the technological potentials of this controversial transhumanist research. report from 2021 Technological Approaches to Human Performance Enhancement For example, the report from 2021 notes that “ ,” and “ ” were all potential applications for genomic editing. adding reptilian genes that provide the ability to see in infrared making humans stronger, more intelligent, or more adapted to extreme environments As , “If successful, .” I reported over two years ago these ‘people’ would have the potential to never tire and think smarter, move faster, jump higher, see farther, hear better, hit harder, live longer, adapt stronger, and calculate quicker than any other human being on the planet If and when humans become fully integrated with machines on a large scale, where will the technology end and the human begin? On the last day of the World Economic Forum meeting in 2020, a discussion about “When Humans Become Cyborgs” attempted to tackle some of the very large ethical questions surrounding bodily integrity and digital ownership of cyborgs. Ilina Singh, professor of neuroscience and society at Oxford, that one of the major concerns from military officers was a sense of ownership and bodily integrity. told the Davos crowd Military officers were concerned over many issues, such as: Do I own my own implant? Does my implant become part of me? What happens when I leave the military? Who pays for my implant? Does my implant get removed? Do I get to keep my implant for life? Does my implant get upgraded? Who pays for that? In the same discussion, National Academy of Medicine president Victor Dzau told the Davos elites that using brain-computer interfaces to augment humans beyond their natural capabilities was crossing the ethical line. “I think you’re in pretty safe ground when you use these technologies for the purpose of curing disease, treating disease, or at least addressing impairment,” he said, adding, “ .” I do think you start crossing the line when you think about enhancement and augmentation What’s to become of the soldiers and government agents that have been genetically edited with superhuman powers once their service has ended? What advantages or disadvantages would people with have compared to the rest of humanity? godlike abilities This article was originally published by on Tim Hinchliffe The Sociable.

The Future of War According to RAND; Cyborgs and Genetically Enhanced Supersoldiers 

RAND অনুযায়ী যুদ্ধের ভবিষ্যৎ; সাইবোর্গস এবং জেনেটিকালি এনহ্যান্সড সুপারসোল্ডার

Die Zukunft des Krieges laut RAND; Cyborgs und genetisch verbesserte Supersoldaten

El futuro de la guerra según RAND; Cyborgs y supersoldados genéticamente mejorados

L'avenir de la guerre selon RAND ; Cyborgs et supersoldats génétiquement améliorés

रैंड के अनुसार युद्ध का भविष्य; साइबोर्ग और आनुवंशिक रूप से उन्नत सुपरसोल्जर्स

RAND による戦争の未来;サイボーグと遺伝子強化されたスーパーソルジャー

RAND에 따르면 전쟁의 미래; 사이보그와 유전적으로 강화된 슈퍼솔저

O futuro da guerra de acordo com a RAND; Ciborgues e supersoldados geneticamente melhorados

Будущее войны по версии RAND; Киборги и генетически улучшенные суперсолдаты

RAND'a Göre Savaşın Geleceği; Cyborglar ve Genetiği Geliştirilmiş Süper Askerler

Tương lai của chiến tranh Theo RAND; Cyborgs và siêu chiến binh được cải tiến về mặt di truyền

兰德认为战争的未来；机器人和基因增强超级士兵

The final frontier of delivery is going autonomous. As online orders surge and customers demand ever faster times, last-mile logistics is transforming at warp speed. Self-driving cars, drones and robots are invading suburbs worldwide, promising to bring goods to your door within minutes. No longer fiction, the vision of ordering coffee on a whim and seeing it arrive piping hot via robot is becoming reality. Need a package ASAP? Drones may soon deliver overhead. Companies like Yandex are accelerating this revolution by developing cutting-edge autonomous vehicles for last-mile tasks. In this article, we'll take a drive exploring the innovations upending last-mile delivery. We'll look at the technologies and companies at the forefront of this rapid change. We'll also peer into the future to speculate how new advances could push instant gratification to new heights. From Horse-Drawn Carriages to Delivery Drones People had been delivering goods for centuries using animals like horses and camels. Later, trains, ships and cars sped things up. But the last mile - getting items from large vehicles to destinations - remained difficult. E-commerce boomed in the late 1900s, creating demand for fast package shipping. FedEx and UPS rose with planes, trucks, and vans worldwide. Yet online orders grew so much that last-mile challenges also increased. Customers wanted speedier, cheaper, flexible options while costs rose for companies. To meet these problems, firms tried new methods. with free two-day shipping. They also did same-day and one-hour delivery, using instead of employees. Amazon has also experimented with drones, robots and lockers too, seeking better last-mile solutions. Amazon launched Prime in 2005 independent drivers The Last Mile: The Final Frontier of Logistics Last-mile delivery is important for several reasons. First, it is a key factor in customer satisfaction and loyalty. According to a survey by McKinsey, 25% of online shoppers would switch to another retailer if they had a bad delivery experience. Moreover, 56% of millennials said they would pay more for same-day or instant delivery. Therefore, offering fast and reliable last-mile delivery can give a competitive edge to online retailers. Second, last-mile delivery is a major cost driver in logistics. According to some estimates, last-mile delivery accounts for 41% of the total delivery cost and 53% of the total carbon emissions. Reducing the cost and environmental impact of last-mile delivery can improve the profitability and sustainability of online retail. Third, last-mile delivery is a source of . As technology advances and consumer behaviour changes, fresh solutions and players emerge in the last-mile ecosystem. For example, startups like DoorDash, Instacart, and Postmates offer on-demand delivery services for food and groceries. Platforms like Uber Eats, Doordash, and Grubhub connect restaurants with customers and couriers. Companies like Yandex, Starship Technologies, and Nuro develop autonomous vehicles for last-mile delivery. innovation and opportunity The Tech Titans of Today: Yandex, Amazon, and Beyond Two companies that stand out as leaders in last-mile delivery innovation are Yandex and Amazon. Yandex is a Russian internet giant that provides services like search, advertising, e-commerce, maps, cloud computing, and self-driving technology. They've been developing autonomous vehicle technology and currently have a fleet of . These cars have driven over 4 million miles on public roads in Russia, Israel, and the US under various weather and road conditions. With this level of maturity and real-world experience, Yandex is considered one of the global leaders in self-driving development. since 2017 170 self-driving cars Yandex also launched their own delivery robot called Yandex.Rover for transporting small and medium packages autonomously. This robotic option could help automate last-mile delivery within their ecosystem and beyond, providing a sustainable way to deliver food and goods. In total, Yandex has invested approximately into their self-driving division. Recently, they launched Yandex.Rover commercial operations in Skolkovo, a major Russian tech hub. Yandex plans to introduce their autonomous services in Ann Arbor, Michigan and Tel Aviv in the near future as well. $150 million Amazon is another dominant player in e-commerce and technology, known for online retail, streaming, cloud services, AI, and smart devices. They've invested heavily in logistics to speed up and improve delivery. Amazon developed their own delivery network called Amazon Logistics which uses stations, sorting centres, transportation providers, and delivery partners to ship packages independent of traditional carriers. Amazon has also introduced autonomous solutions like , which aims to deliver packages by drone within 30 minutes, and Amazon Scout, a six-wheeled sidewalk robot for navigating neighbourhoods and dropping packages at doorsteps. Other experimental delivery methods from Amazon include in-car/home delivery with and locker/counter pickup with Amazon Hub. Through technological capabilities and their massive customer base, Amazon has become a major force in last-mile delivery. Amazon Prime Air Amazon Key Beyond Yandex and Amazon, companies like , , and are innovating as well. Starship designs small self-driving delivery robots for food, groceries and more across Europe and North America. Nuro partners with retailers to autonomously deliver goods like groceries and prescriptions using their vehicles. And Zipline runs what they claim is the world's largest drone delivery network, transporting medical supplies in Africa and beyond. In the next section, we'll examine some current last-mile delivery case studies. Starship Technologies Nuro Zipline Case Studies from the Front Line: Last-Mile Delivery Today Yandex.Rover in Serbia In June 2023, , Serbia, marking the first time it operated outside of Russia. Yandex partners with local restaurants, cafes, and supermarkets to offer fast, convenient food, grocery, and item delivery to customers via the Yandex app. Customers can track the robot's location and estimated arrival time. Using cameras, lidar and GPS, Yandex.Rover autonomously navigates sidewalks, crosswalks, and traffic lights. Speakers and a screen allow it to communicate with pedestrians and drivers. Its cargo compartment only opens with a unique QR or PIN code provided to the customer. Yandex launched its delivery robot Yandex.Rover in Belgrade This launch was part of Yandex's European expansion strategy. As a leading provider of search, maps, taxi, and food delivery services in Serbia, Yandex aimed to highlight its technological capabilities and offer a unique value with Rover as well. Amazon Prime Air in US, UK, and Italy Amazon Prime Air will integrate drone deliveries into Amazon’s existing fulfilment network, deploying from Same-Day Delivery sites. Amazon customers in Italy, the UK, and an additional U.S. city will soon have the option to get their packages delivered by a drone beginning in late 2024. The Prime Air drone delivery system is expanding to international locations and adding a third city in the United States by the end of next year— specific cities in the U.S. and abroad will be named in the coming months. Zipline in Nigeria In October 2022, through partnerships with the Kaduna State Government and Gates Foundation. Zipline delivers blood, vaccines, medication, and medical supplies from its Kaduna distribution centre to over 1,000 health facilities across the state via 120 km/h flying drones carrying 1.8kg payloads within 30 minutes in all weather. Zipline launched drone services in Nigeria Zipline's Nigeria launch expanded its mission begun in Rwanda in 2016 and Ghana in 2019, where it delivered over 1 million vaccine doses and saved thousands of lives. It aimed to further support universal healthcare in Nigeria. Upcoming Technologies: What’s In the Pipeline? Technology is one of the main drivers of innovation and disruption in last-mile delivery. As technology advances, novel solutions and possibilities emerge that could enhance the efficiency, convenience, and sustainability of last-mile delivery. Here are some of the upcoming technologies that could have a significant impact in the coming years: Hyperloop is a proposed mode of transportation that involves sending pods or capsules through a network of tubes or tunnels at shockingly high speeds, up to 1,200 kilometres per hour. Hyperloop could enable fast and low-cost transportation of goods over long distances, reducing the need for trucks, planes, or trains. Hyperloop could also connect urban areas with rural or remote areas, expanding the reach and accessibility of last-mile delivery. : Hyperloop Blockchain is a distributed ledger technology that enables secure and transparent transactions among multiple parties without intermediaries. Blockchain could improve the traceability, accountability, and efficiency of last-mile delivery by enabling real-time tracking of goods, smart contracts for payments and deliveries, and decentralized platforms for peer-to-peer delivery. : Blockchain 3D printing is a technology that enables the creation of physical objects from digital models by depositing layers of material. 3D printing could revolutionize last-mile delivery by enabling on-demand and localized production of goods, reducing the need for inventory, warehousing, and transportation. 3D printing could also enable customization and personalization of goods, enhancing customer satisfaction and loyalty. : 3D Printing Biotechnology is a technology that involves the manipulation of living organisms or biological systems. Biotechnology could transform last-mile delivery by enabling novel solutions for packaging, preservation, and delivery of goods. For example, biodegradable packaging made from algae or fungi could reduce waste and environmental impact. Bioengineered foods or medicines could extend shelf life and improve quality. Biosensors or biometrics could enable secure and convenient delivery verification. : Biotechnology However, challenges exist - technical and regulatory hurdles, social acceptance, ethics, and cybersecurity risks require careful evaluation before adopting unfamiliar concepts. Strategic Shifts: Predicting the Unpredictable While technology drives change, unpredictable human factors also impact last-mile delivery's future. Shifting consumer behaviours, economic conditions, environmental concerns, politics, and natural disasters create uncertainty, with opportunities and risks. To adapt amid this complexity, companies must strategically pivot. Transitioning focus from products alone to customers' experiences demands deep understanding of needs, personalization, and loyalty-building through positive impact. Transitioning from ownership to access alters business models, as shared subscriptions and rentals replace individual purchases in the circular sharing economy. Platform ecosystems boost availability. Moving operations away from centralization delegates control and fosters innovation through distributed localized partner networks, peer-to-peer crowdsourcing, and community cooperation. However, achieving the right product-service balance with these shifts requires trade-offs. Implementing changes across dispersed stakeholders introduces risks that must be diligently governed. Incentives and resource coordination become more intricate. Careful consideration weighs consequences before wholesale adoption. But navigating humanity's disruptive course demands agility and vision. Strategic flexibility positions resilience amid uncertainty, preparedness navigating both risks and opportunities ahead. With responsibility and diligence, last-mile leaders can help deliver the future people need. The Future is Now One thing is clear - we are witnessing the dawning of a new era. An era where imagination meets innovation, where science fiction becomes a science fact, where the impossible becomes possible. Yesteryear's visions of drones, robots and self-driving vehicles delivering goods on demand have already transformed into today's reality. Pioneers like Yandex, Amazon and Starship have pulled the future into the present and set us boldly on a course we could only dream of just a decade ago. What will the next decade bring? It is impossible to say for certain, but if history is any guide, it may surpass even our most outlandish speculations. The innovations will continuously reshape life as we know it, delivering value to all in their wake. As for the rest of us, our role is clear - embrace change with optimism and curiosity. Keep an open mind for what is to come, everyone!

The Last-Mile Delivery Revolution: What’s Next on the Horizon?

Introduction I first thought about speaking at tech conferences as a way to get a free ticket – let's face it, they're not cheap. But what started as a practical move turned out to be a journey of incredible learning and networking. Over time, as I spoke at more than 19 events, I realized these conferences were more than just stages to share ideas; they were opportunities to connect with CEOs, top experts, authors, and so many inspiring people. Back then, my experience included only teaching JavaScript to my colleagues at work and presenting startup ideas at local hackathons. These experiences were my stepping stones into the world of tech conferences. Today, with a wealth of presentations behind me, I want to share why stepping onto that stage is so rewarding. It's not just about discussing cutting-edge topics like programming techniques, AI advancements, boosting productivity, or nurturing startup growth. It's about the interactions, the shared knowledge, and the diverse perspectives you encounter. In this guide, I'll take you through how to kickstart your journey in conference speaking and make the most of it. Advantages of becoming a conference speaker opportunity to meet new people from your field; share what you're working on and get inspiration for new projects. Listen to other speakers who are way better than you in engineering. I’ve met notable figures in engineering through conferences and had a chance to ask them questions about how they work or run their companies. I know I wouldn’t have a chance of meeting them anywhere else. TOP ONE: : speaking at conferences provides you an opportunity to present your expertise, skills, and background, potentially strengthening your current job position and boosting credibility with both existing and potential clients. Your presentation typically undergoes a selection process conducted by an experienced panel of professionals on the program committee, so you get the chance to see if there's any audience for your knowledge. From my experience, when applying for jobs, interviewers really appreciate some background connected with public speaking. And finally, once you become more recognizable, further speaking opportunities are unlocked, and organizers start to reach out to you themselves. Getting valuable credentials : participating in a conference is a good way to meet and run your ideas through experts. Or expand your professional network if you're into LinkedIn lingo. You can (and I recommend doing so) engage with other speakers, event coordinators, and sponsors. This may lead to potential collaborations and career opportunities. Sharing your contact information for future communication is a must. After some of the conferences, I got offers to run thematic courses in some companies, so once the market sees you as an expert in the field, you can really expand your brand. Collaborating : when preparing your presentation, you have the chance to structure your know-how in an organized and effective way. Additionally, while presenting your talk, you practice the delivery of your hard-earned knowledge, and you get a chance to be challenged by participants’ questions related to your topic. Preparing presentations helped me look critically at my work and improve how I do things. Reinforcing your skills : you can distribute your presentation slides to the audience through social media, post your talk video on platforms like YouTube, or interact with individuals involved in the event through LinkedIn and other platforms. I also noticed that even though I never promoted a product, a book, or anything in particular, there were always some new followers or contacts on all my platforms. Expanding your online presence How to find conferences to participate in? To find the top events to speak at, I do a brief scheduled conference research every two weeks. I search for IT conferences that match my area of expertise and check if they're accepting talk proposals. For international conferences, having a speaker profile on a platform like is the best way to discover new, interesting events. https://sessionize.com/ I also recommend checking out the following websites: https://dev.events/tech https://www.eventyco.com/events/conferences/tech https://confs.tech/ I am based in Poland, Europe, so I also look at local events, and my go-to place is . Every country will likely have an event aggregator like that. Crossweb At this point I also get directly invited by past event’ organizers I spoke at or by conference managers who saw me on other event's websites. Once I find a conference I like, I either apply right away (if I have a suitable talk ready or in the pipeline), or I set a deadline for myself in Notion (note-taking/project management app) to create a proposal. To keep track of all this, I've made a special section in notes for conference applications. It helps me see which events I've applied to, whether the organizers accepted my proposal (or not), and the topic of the talk I submitted. When you take part in conferences regularly, it's easy to get lost in all application forms and emails, so this system keeps everything organized and makes sure I don't forget or miss out on opportunities. What can you prepare prior to applying? To make applying for conferences easier and faster, I organize important information in one place. This way, I can quickly access it whenever I need it. For each conference application, you usually need to provide: : your email, phone number, Twitter and LinkedIn handles, a profile picture, your current job title, and a short bio. I have all this information saved in a dedicated section in Notion, and I just copy and paste it when I apply for a conference. Basic data you provide should include details about your current job, any extra projects you're involved in, and fields of expertise you feel confident about and can present at the conferences. As an example, here's my latest bio for reference: The bio Software Engineer Manager at Netacea, an AI cybersecurity SaaS startup based in the UK. Creator of sentimatic.io - a product for analyzing emotions and content of customer conversations based on AI technology. I run a blog on horosin.com, where I write about topics related to programming, AI products, and startups. I am professionally and personally interested in biotechnology, medicine, space technologies, filmmaking, and literature. I enjoy sharing knowledge in the field of programming and AI-based solutions while gaining inspiration from discussions with new people I meet. : I keep track of all my talks and ideas in Notion, so if I'm short of inspiration, I simply update it and add necessary changes instead of starting from scratch every time. Overview of the talk you want to present : I keep a record of my public appearances on my blog at https://horosin.com/conference, and I always link it as a part of my application. It's important to have a portfolio that shows your experience, as it makes you a more reliable candidate. Here's a note I attach: Past conference experience I have spoken at several conferences so far. I like talking about programming, startups, innovative products and advancements in the AI field. Here is a link to all my conference experiences gathered: https://horosin.com/conference I have also been on the program board of a 2021 4developers Live conference. I was responsible for the selection of talks for the Python track. How to prepare and present a talk? Successful conference participation depends mostly on what and how you present. Take the time to establish your personal strengths, define what you’re good at, and narrow down your field of expertise. Find something in your work that is valuable to share with your audience and make sure the content is genuinely useful to your listeners. Remember that talking about your mistakes can be as beneficial as celebrating your successes. Consider your failures as lessons that can prevent others from making similar mistakes. I've done this numerous times, for example, while discussing the five startups I failed at. I talked about this at three different conferences, sharing my business journey and what I learnt from it . It is, to this day, one of my most popular talks and blog articles. https://horosin.com/i-launched-6-startups-in-8-months-and-5-of-them-failed While preparing the slides, I follow a process: Craft an outline for your speech. Draft your initial version. Refine your draft, brainstorm fresh ways to share your ideas, and then settle on the final version. Create slides for your presentation. Improve your presentation with engaging elements such as data, graphics, personal anecdotes, or connections to certain individuals to make it stand out. Remember to practice your speech, watch your timing, and make adjustments as necessary to fit the given time frame. During your presentation, don’t forget about a few key tips while still trying to stay natural. It's not necessary for everything to go according to the script; however, small adjustments can improve the final result: : Try to pay attention to how you move. Use your body to show your ideas and to better connect with your audience. Move around the stage, keep eye contact with various listeners, and use hand gestures or facial expressions to underline some main points. Body language : Your main goal should be to provide value to the audience, not to sell products. If you give people what they came for, they'll want more from you. You just need to tell them how to find it. I put my social media information on my presentation slides, and sometimes, at the end of the talk, depending on the conference, I share new product ideas connected with the speech. Focus on your personal expertise : Keep the conversation going. Plan a time for questions and answers with the listeners. This part can help you look at your material from different perspectives. You can get authentic feedback on your work. Get the audience involved : Don't forget to ask for thoughts and suggestions. It can help you get better for your next talk and develop your portfolio. At some conferences, feedback is collected through forms and later visible in your speaker’s profile. Otherwise, simply collect it by directly sharing feedback forms. Ask for feedback While presenting, never downplay yourself. If you were selected to speak, then your expertise is enough. You also put your name and time on the line. We're all busy and trying the best we can. If you "had no time to make the slides pretty", don't say that; it's annoying to people that give you their attention. Just pretend your lack of design polish is just your cute nerdiness. Much better effect. Or better, just have a look at my article about MARP so your slides are never ugly again and take 10x less effort: https://horosin.com/effortlessly-create-powerpoint-presentations-with-chatgpt-and-marp How to get the most out of conferences (before and after)? OK, you got an acceptance email, and now what? If you want to get the most out of the conference, it's important to plan ahead. Here's a simple guide on what to do after being selected as a speaker. It's a process I loosely follow. If you do any of the steps, you're already ahead. All that said, the key is a great submission and a value-packed presentation. Everything below is pointless without those. 3 weeks before the conference Start researching the people involved, like the event organizers, other speakers, and sponsors. Identify those you'd like to connect with and reach out to them online. Contact them to schedule a meeting or chat before the event. 2.5 weeks before the conference Share any promotional graphics the organizers provide, which usually feature your photo, topic, track, and maybe a discount code. Publish content on your social media and tag people involved. You can also create your own announcement post if needed. 2 weeks before the conference Consider talking to the organizers about creating a post for their social media. This could be a video inviting others to the conference or a short post about your talk. 1.5 weeks before the conference Create a teaser post with a summary and key points from your presentation to generate more interest. This is a good way to share some knowledge online in preparation for the event. Provide real value; don't advertise. 1 week before the conference Make sure your presentation is well-prepared. Upload your slides online so you can easily share them with participants after your talk. Also, direct people to your social media for any updates. On the day of the conference, connect with as many people as you can, especially those you researched earlier. Attend other talks, take notes, and share your thoughts about them on social media. Take photos during other speakers' presentations and share them later to provide fresh content for their social media. Engage with your audience after your presentation, perhaps over a coffee. Respond to social media posts related to the conference and share your behind-the-scenes impressions. Now that the conference is over, expanding your network and benefiting from participating doesn't really stop. Here are some things that I do afterward. 1 Day After the Conference: Share Your Thoughts After the event, post your impressions on social media. Share what you learned and your general thoughts on the conference. Tag people to start discussions. Here is an example of my LinkedIn post, which I published after speaking at Devoxx Poland: https://www.linkedin.com/posts/horosin_buildinpublic-startups-conference-activity-7070351872594690048-urgz/ As you see, it was quite successful - I got 52 likes with only 500 followers I had at a time. 2 Days After the Conference: Update Your Portfolio Add the conference experience to your speaker portfolio. This could be a website, LinkedIn article, your resume, or wherever you gather your accomplishments. Keep a list of the talks you've given, including dates, titles, and event names. It's a good place to share notes, slides, and related materials from your talks. 5 Days After the Conference: Share Your Presentation Materials Share the slides you used in your presentation. You can post the original materials or create a quick guide on the topic you presented. Sharing knowledge is one of the key points of being a conference speaker, so I try to come forward to my listeners with as many useful sources as possible. 10 days After the Conference: Gather Feedback Collect feedback from the audience and organizers. You can use social media polls, direct messages, or check for opinions on your speaker profile. Reading feedback helps you find areas for improvement and can be useful for future conference applications or negotiations regarding payment. 2 Weeks After the Conference: Reuse Your Content You can reuse your slides by turning them into articles or posts or applying feedback and refining them for another conference. I post articles related to my talks on my blog, so they're always available for reference. Money. How much does it cost? Can you get paid? Usually, the conference will cover all your travel expenses and admission. You will also get invited to speaker dinners and extra networking opportunities. Some events may ask if you have an option to pay for travel yourself or ask your employer for coverage. It will raise your odds of being admitted. My experience with traveling for conferences is mixed. Some booked very low quality, scary even, accommodation. These events are often sponsored by big companies and generate a lot of profit. Saving on speakers feels unacceptable to me, as they usually contribute to the event's success for free. I lived abroad for some time, and a few conferences paid for my flights back home in order to speak. Getting paid? If you have a lot of experience, are an established author, and work in a great company - yeah, possible. Usually, a good conference will pay for a few speakers, especially the keynote ones. Many, even very experienced ones, will just get their expenses covered, but it's a welcome enough benefit for them and should be for you. Speaking is often a community contribution, a way of giving back to the community. Do you have to take time off to speak at a conference? My arrangement is usually to present as a part of my job. The company I work with always gets mentioned; I try to generate sales leads and do a bit of hiring at every event I attend. I also provide photos and short written reports for the marketing department so they can prepare some content for the company's social media channels. Don’t be afraid to talk to your manager to work out the details. You being at a conference as a speaker is a pure benefit for the company - you get free training and generate free publicity. Make sure it is well understood. I’m also spending a bit of my own money on the whole process. I work with a part-time personal assistant who helps me, among others, with managing talk submissions and refining slides from the design point of view. Conclusions Summing up, I recommend taking part in conferences as a speaker. You get the opportunity to expand your network, organize knowledge, and practice public speaking. Making conference research a part of your regular tasks will result in more event opportunities. I did so and the number of conferences I took part in 2023 is higher than ever before. If you prepare for your speech in a smart way, you can reuse your content. Following a few simple steps before and after the conference will help you make the most out of your presentation and will result in the development of your personal brand. For the next year, my plan would be to speak mostly at international events so I can mix it with some traveling. I'm also aiming to get some number of paid gigs, as I have plenty of experience to do a solid agenda-boosting keynote. Do you plan to speak at any tech conference? Any stories or thoughts? Subscribe to my profile by filling in your email address on the left, and be up-to-date with my articles! Don't forget to follow me on Twitter and subscribe to my blog’s for more tips and insights! @ horosin_ newsletter If you don't have Twitter, you can also follow me on . LinkedIn Also published . here

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