Finding Genius Podcast

Bio: Lauren Maffeo has reported on and worked within the global technology sector. She started her career as a freelance journalist covering tech trends for The Guardian and The Next Web from London. Today, she works as a senior content analyst at GetApp (a Gartner company), where she covers the impact of emerging tech like AI and blockchain on small and midsize business owners. Lauren's research and writing have been cited by sources including Forbes, Fox Business, The Atlantic, and Inc.com. She has spoken at events including Gartner's Symposium in Florida, The Global Talent Summit at ETH Zurich in Switzerland, Women Techmakers Montreal in Canada, and Mashable's Social Media Day. In 2017, Lauren was named to The Drum's 50 Under 30 list of women worth watching in digital. That same year, she helped organize Women Startup Challenge Europe, which was the continent's largest venture capital competition for women-led startups. Lauren Maffeo holds a certificate in Artificial Intelligence: Implications for Business Strategy from MIT's Sloan School of Management. She has consulted and reported as a senior content analyst for GetApp, covering the influence of various emerging technologies, such as blockchain and artificial intelligence, on small to midsize businesses. Maffeo has extensively studied machine learning, natural language processing, and robotics. Maffeo discusses how the perception of AI can sometimes be that it is a monolithic entity devoid of humanity, but in fact, AI has a significant swath of use cases that make it ideal for many human-powered, customer service oriented businesses. Maffeo states that AI is often best when introduced alongside human workers to enhance the overall workflow. Many businesses state that they simply don't have the staffing necessary to implement AI projects, while others state that they have difficulty in defining their overall AI strategy. Still, other businesses state that they are unsure of how to get started with AI altogether. Ultimately, at current, AI is touted as a transformative tool, but hype aside, some businesses are simply struggling to understand how to best utilize it. The technology consultant outlines some of the aspects of AI that will become more advanced and specialized in the coming years, such as AI's social perception and context. While automation with AI will facilitate many industries, such as construction or other industrial types, Maffeo states that the perception of AI taking jobs from human workers is skewed. In fact, in many industries, it is a lack of available human workers that is spurring the advent of AI in certain workplaces. Maffeo discusses the potential impediments to complete implementation of AI in a wider scope. Cost would be an issue, but even before the consideration of cost, there are some other issues to consider. The topic of 'use cases,' essentially knowing how AI can be used effectively, is a fundamental issue. The need for quality data scientists is also a critical issue—to regulate data in an AI system to ensure that it is healthy, unbiased data. Additionally, high-level architects that are capable of building networks become an issue simply because they are in demand but are not readily available. Maffeo provides further insight into some of the areas of AI that will proliferate. Innovations in advanced AI such as chatbots will be a growing industry in the coming years. Predictions indicate that as many as 10% of new IT hires will be tasked with writing bot scripts as chatbots become ubiquitous in online commerce. Machine learning will allow chatbots to interface with customers at an advanced level as chatbots can access a wealth of data about the user. And although current data demonstrate that the majority of people prefer a human interaction, as AI refines the chatbot experience the expectation is that users will acclimate to the advancing technology.

Matthew Osman, Co-founder of Legit (legitpatents.com), discusses his company's advanced AI technology that allows inventors and developers, from every industry, access to critical information and knowledge that can save time and money. A man of many accomplishments, Matthew was the youngest VP of a one billion dollar hedge fund in London, where he primarily focused on tax structuring and credit strategies. While working towards his degree from the University of Oxford, Osman studied philosophy, politics, and economics extensively. Osman's company, Legit, is a new brand of AI company that focuses on natural language processing and evolutionary computation. As Osman states, the goal of his company is to turn literally anyone into an actual inventor. Legit builds applications that are powered by natural language processing for engineers, researchers, and scientists that aid in the identification of their work, to assess whether it is unique. Legit's engines look deeper into identification processes, going beyond the elementary keyword approach, delving into conceptual similarities. Legit can evaluate a project in real time, comparing it to as many as thirty million other documented projects and prototypes, thus giving the creator a true sense of their work's originality. But beyond the comparisons and real-time evaluation, Legit's technology can also suggest various means to increase an invention's uniqueness, offer suggestions of potential collaborators, and recommend possible buyers or licensors. Essentially, Legit can walk with inventors through their initial ideation phase all the way to patent. Whether you're a solo inventor working out of your garage or a research and development professional employed by a billion-dollar corporation, some needs are the same for both, in that every inventor is benefited by knowledge of what's already in the market or in the pipeline. Legit's app saves time and decreases waste in R&D by gathering the important information necessary to suss an idea's originality and determine how valuable the invention could be in general, to maximize outcomes. With 2.2 trillion dollars expected to be spent in the coming year on R&D, it's clear that any inventor or company must be tapped into the development market to ascertain their inventions' particular characteristics of value and originality. Osman explains how Legit's AI is trained on an extensive corpus, or collection, of technical literature such that their technology can make astute assessments based on the desired goals of similar projects, even if there are no shared keywords between them in their stated objectives or descriptions. As the push for new innovative products is certainly increasing, and technology is expanding, the need for specific knowledge is perhaps at an all-time high, and Legit's advanced AI can provide that knowledge.

Alicia Kavelaars, Founder, and CTO of OffWorld (offworld.ai) discuss her company's efforts to build robotic technology for extreme environments, with advanced machine learning and AI, to assist humans to be offworld. Offworld, roughly defined as 'away from earth' is the core point of Kavelaars' company's mission—to enable "smart robots working under human supervision on and offworld, turning the inner solar system into a better, gentler, greener place for life and civilization." While experimentation in space is costly, Kavelaars explains that much of their testing is done in more financially practical extreme environments such as underground mines and seabeds, etc. OffWorld's initial prototypes focus on mining in extreme environments and will be tested in underground mines first, but these robotic workforces will be extremely helpful in a space environment for colonization preparation efforts. Kavelaars' robot workforce is already designed for an end-to-end mining solution. From mining through processing, OffWorld's robotic workforce is capable of handling the job. OffWorld's robots can go deeper underground, to mine in ventilation and extreme temperature conditions that humans could not withstand, and of course robots can work 24 hours a day for continuous workflow. With thousands of robots in a workforce, Kavelaars expects to move humans to supervisory roles, out of harm's way, and allow advanced machine learning to continue to enhance the robots' effectiveness. OffWorld's robotic workforce is fully autonomous, end to end, but if a robot in the workforce experiences a contingency situation in which it cannot make the assessment on its own, human supervisors step in and handle it. Kavelaars explains how OffWorld's robots operate independently, in that they are not centrally programmed with a hive mentality, but perform as solo operators with a heightened awareness of the other robots working alongside them. This design helps to alleviate potential single-point failures as Kavelaars' robots will recognize failures and independently, but with a collective understanding, support any one-off failures. The robotics founder expounds upon her desire to take her robotic workforce to space and the preparation to make them fully autonomous in advance of their mission. Kavelaars' team employs machine learning to help robots evaluate precise techniques for proper mining, to allow the robots to vary their approach based upon arising conditions, as opposed to simply inputting algorithms that would not allow for adjustments. Additionally, the CTO and founder discuss her company's plans to introduce robotic workforces for other areas of industry as well, such as large construction projects. As robotic workforces can work independently and autonomously, but can also work in tandem with humans, robots can significantly increase efficiency in many industries with challenging environments. And as machine learning advances and sophistication of robotic technology is refined even further, robotic workforces will be able to master practically any industry-type tasks.

Coin-Energy has developed a system as the World's first mobile full-service mining solution provider, based on low-cost renewable electricity which can be located any place on the Globe: hydro, solar, wind. Our Hosting Mobile Miner Units (HMMUs) are modified 20' reefer sea containers, equipped with state of the art mining hardware. Mining-units are indefinitely scalable due to efficient, available, low-cost hardware.

Jason Barkeloo - Founder of Knowbella tech joins Future Tech Podcast. Knowbella Tech www.Knowbella.Tech crowdsources scientists around orphan/dormant intellectual properties (IP). By enabling researchers to collaborate on a web-based platform, science and innovations should be advanced. After its SEC-compliant Token Generating Event (TGE also frequently called ICO), Knowbella Tech will launch its web-based collaboration platform. Knowbella Tech licensed its platform from Open Therapeutics (https://Therapoid.net) for crowdsourcing all non-therapeutic intellectual properties (IP) The platform freely provides researchers, particularly the underserved, IP, grants, free lab equipment, manuscript development tools, mentors, and preprint server.

Lasya Marla, Director of Fusion AI at Lucidworks, a search technology company that utilizes AI to better understand human intent, provides a thorough overview of the data optimization improvements AI-based technology is delivering. Lucidworks' platform is comprised of three major areas, Fusion AI, Fusion App Studio, and Fusion Server. Fusion AI facilitates customer experiences and is driven by signal capture and relevance boosting using advanced AI machine learning. Fusion App Studio helps to create made-to-order, data-heavy searches and applications for the web and mobile technology products. Finally, Fusion Server is a search engine and NoSQL data store that provides immediate access to a person's or company's data, available when it is needed, and it can be scaled for the needs of the user. The technology director delivers an overview of ecommerce and retail website searches and queries, as well as other types of customer-based websites, and how advance machine learning can greatly enhance their users' experiences. Marla explains some of the reasons why search results can be less than desired, such as one of the dominating issues—the engine does not know what the user is searching for thus it cannot perform efficiently. She gives us an insightful look into the inner-workings of a typical search, and the problems that could arise that compromise or devalue the end results. One such issue, Marla explains, could be within the algorithm itself, and its ranking of less desired results on a higher level. For example, when one searches for a particular product, a search engine may rank accessories for that product higher in the search results due to the fact that the product name may be listed more often in the product's accessories' descriptions. This could result in a user receiving higher ranked product accessory links than the links to the actual product itself. The Fusion AI director discusses the demands that users place on search engines and how users' expectations are driving the need to develop engines that are intelligent. Marla states users expect much more; users want recommendations, and they want the engine to understand their intent, to be able to understand misspellings, etc. and still deliver relevant results. She expounds upon the methods an individual or company can use to train a made-to-order search engine model to meet the specific needs of their site's users. One such method would be to utilize modified data that is then applied and implemented into the associated query pipeline. Marla explains how companies like Amazon have raised the bar for user search experiences, but many of the features that users love on sites like Amazon, such as user recommendations can be implemented for any business site. Companies and businesses can run recommendation algorithms on their sites' search engines to increase user enjoyment, efficiency of experience, and ultimately keep the user on the site longer. Marla explains the process an individual would go through in order to utilize Lucidworks' advanced technology algorithms. For example, if an individual wanted to introduce specific algorithms onto their site and search engine, perhaps a head/tail analysis, query intent classifier, personalization module, recommendations module, etc., the individual would follow simple steps in order to retool their engine. Essentially, to migrate an ecommerce or other site into Lucidworks' platform an individual would first provide Lucidworks with all their actionable data, including valid signal data comprised of relevant user interactions. Next, they would select the desired algorithms to be applied, and then align their front-end site with the API endpoints generated by Lucidworks' proprietary technology. By streamlining the process, Lucidworks can facilitate a company's needs by allowing the retooling to be somewhat automated, in that a search developer won't need to necessarily understand what is, 'under the hood,' in order to keep it online and efficiently running. While Lucidworks' technology-based solutions for advanced search engines can be useful to most any individual or business seeking to enhance their users' experience, Marla explains that the key ingredient in the search engine soup is the user interaction data. Without user interaction data, the algorithms may enhance the efficiency to a degree but it is this specific data that really gets the engine running at top performance, and the more data the better!

Kevin Holden is the Head of Synthetic Biology at Synthego. Mr. Holden holds a PhD in Microbiology from University of California, Davis. He has over 10 years of experience in the biotechnology arena, with specific study and research in synthetic biology as well as in engineering, notably—metabolic pathways in microbes. Synthego's primary work is focused in software and synthetic RNA kits designed for CRISPR genome research and editing. Synthego uses AI and machine learning to assist researchers and developers with automation for genome engineering that provides for efficient research with consistent results, at a price point that allows for savings. With a strong background in engineering, Synthego's team applies engineering principles to synthetic biology practices, especially for gene editing. Holden's company, Synthego, works with hardware and software and utilizes advanced machine learning to assist in research platforms and technology, such as the CRISPR-Cas9 genome editing technology. CRISPR is the acronym for Clustered Regularly Interspaced Short Palindromic Repeats, which are the distinctive feature of a complete bacterial defense system and the foundation for CRISPR-Cas9 genome editing technology. Synthego's hardware platform allows for the synthesization of RNA, to guide CRISPR technology to a specific place on the genome in order to make an edit. Holden discusses how Synthego's automation allows scientists to skip steps traditionally needed for method development and thus focus their efforts more immediately on their actual research, as Synthego can provide gene edited cells directly to them. The synthetic biology expert explains some of the various areas that his company is currently focused on. In particular, Holden's team is very excited about the potential for their work to be of particular use to researchers working with monogenic, or single gene, diseases, including single gene mutations. Miraculously, cells can be extracted from a patient, edited, tested, and then ex vivo transplanted back into a patient to cure the disease. Edited, corrected cells, once implanted into the patient then grow new cells void of the mutation that was once causing the disease. Holden also provides a detailed analysis of their work in the amazing area known as CAR T-cell therapy. CAR T-cell therapy is the process in which a patient's immune system cells, or T cells, are edited so they will then begin to attack cancer cells upon reintroduction into the body. As the microbiology PhD explains, enabling scientists to obtain gene-edited cells for research will greatly facilitate, and accelerate, the complex study of disease and thus allow for new therapies to become available to the public sooner. Synthego's tech decreases time ordinarily spent on model building so scientists' efforts go directly into the research. And Holden explains how AI algorithms are best utilized within large data sets in order to train models. But perhaps one of the most significant uses of this technology will be in the breeding of plants, to engineer them to produce more efficiently, become resistant to disease and even drought, and thus aid in providing needed food for the world. With so many uses for synthetic biology practices and gene editing, it's clear that engineering-based companies such as Synthego will be riding the wave of many coming breakthroughs in medicine and science for years to come.

Christopher Brown is the author of Tropic of Kansas, a dystopian novel that was a finalist for the 2018 Campbell Award for the best science fiction novel of the year. His novel Rule of Capture, the beginning of a series of speculative legal thrillers, is forthcoming from Harper in 2019. He was nominated for a World Fantasy Award for the anthology Three Messages and a Warning: Contemporary Mexican Short Stories of the Fantastic. His short fiction and essays have appeared in a variety of magazines and anthologies. He lives in Austin, Texas, where he also practices technology law.

David J. Gunkel (PhD) is an award-winning educator, scholar and author, specializing in the study of information and communication technology with a focus on ethics. Formally educated in philosophy and media studies, his teaching and research synthesize the hype of high-technology with the rigor and insight of contemporary critical analysis. He is the author of over 50 scholarly journal articles and book chapters, has written and published 7 influential books, lectured and delivered award-winning papers throughout North and South America and Europe, is the managing editor and co-founder of the International Journal of Žižek Studies and co-editor of the Indiana University Press series in Digital Game Studies. He currently holds the position of Professor in the Department of Communication at Northern Illinois University (USA), and his teaching has been recognized with numerous awards, including NIU's Excellence in Undergraduate Teaching and the prestigious Presidential Teaching Professor.

Rise Housing is a social impact company using cryptocurrency (RSE) to tokenize buildings. Rise Housing allows tenants and everyday investors to be able to buy equity in real estate, one token at a time, without any lending or interest rates involved. The platform creates liquidity for the current asset owners of large, multifamily buildings, without enduring the expense and wasted time of the traditional selling process. A currency is only as strong as its circulation and what it is backed by, and our security token will not only be used by large real estate investors looking for a leaner way to liquidate, but we are positioned to be in the hands of otherwise disengaged tenants and small investors, creating high transaction volume in a new global asset class.