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Xcellbio has developed a proprietary cell control system for use in research, drug development and regenerative medicine. The founders discuss their work in the control of tumor cells, stem cells and immune cells. Xcellbio's main focus is the growth of primary human cells outside of the body, which can then be trained to attack disease-causing cells, then returned to the body to eliminate the disease. Their technology is currently in use for cancer research.
Perry Marshall, noted science author of Evolution 2.0, and electrical engineer by trade, leads us on an interesting journey through the science and theory of life itself.
Marshall states that we are only just beginning to grasp the natural genetic engineering that is literally going on all around us daily. He explains how traditional theories quite often offer that occasional positive changes or mutations have the power to populate the earth with diverse life forms; however, this isn't accurate. According to Marshall, cells are actually re-engineering themselves all the time. Many traditional evolutionary theorists push forward their theories of randomness, that nature is stupid and purposeless, but Perry Marshall affirms that their theories are often rooted in an atheist agenda and are simply not true. According to Marshall, cells, plants, and animals are capable of evolving via their own innate intelligence.
Marshall expounds upon classifications of genes, such as select genes that adjust to their environment. In fact, a cell can seek out another cell or cells that may offer the specific DNA that cell needs in order to build structures to advance its growth, or protect it from an intruding outside organism. Essentially, nature is exponentially more sophisticated than we are taught.
But as we consider that nature itself may be intelligent, it brings to mind thoughts of where does this intelligence come from, and naturally this leads to a discussion of God. And the science author provides an interesting discussion on the relationship between science and God as he delves into historic regimes and their political doctrine. Lenin, Stalin, and Mao, for example, at the core of their dogma was the absence of God, and Marshall states that this was a necessary element of their rise to power. For dictators such as these could never have risen to power or maintained their power if forced to contend with religious scholars and people of faith in general. As such, religion was eradicated, churches were burned, and lives were destroyed in order for these despots to grab hold of the power they sought. Ultimately, as Marshall states, people who believe in God will never allow the government to even approach the power of God. And this is why regimes such as those mentioned, and others, seek to build their power upon a foundation of which faith is not a structural component.
Error detection and error correction, cells have the capability for this and more. As Marshall states, evolution is essentially a software engineering problem, and when forced to deal with a stressful situation cells can innovate and actually reprogram themselves. And these cells, which function in the same way, control our immune systems and physiology. A cell in distress will seek out a partner, pull what it needs from that partner cell, and then reproduce daughter cells that solve the problem. In terms of efficiency, one bacterium can perform more programming in twelve minutes than a team of software engineers could perform in twelve weeks.
With the push to advance AI and machine learning reaching a fevered pitch, Marshall states that we could perhaps benefit from simply studying cells. Biomimicry, which is the design and production of materials, systems, and elements patterned after biological organisms and their internal processes, is an accelerating field, as scientists have learned that the best ideas often come from nature.
As an engineer, Marshall believes that true understanding cannot come until you can actually build it. With that in mind he relates the example of the creation of life, in that theories exist that arbitrary entities simply banged around against each other and then randomly created a cell. However, Marshall affirms that until they can produce an environment that can demonstrably create a cell on its own, that their theories of random creation of life simply are stories they've fashioned, and are not in any way based in scientific evidence whatsoever.
The engineer discusses some of the various problems and impediments that could arise with gene editing in the coming years and how researchers' preconceptions can greatly impact advances. As Marshall imparts, in the long run, evolutionists underestimate the power of nature and creationists actually underestimate the power of God.
Based in the heart of Silicon Valley, ZL Technologies (ZL) is an industry leader in enterprise-class information governance software. The award-winning ZL Unified Archive® is the industry's most comprehensive information governance solution, combining analytics, eDiscovery, compliance, records management, and storage optimization under one architecture.
ZL has been recognized as a Leader in Gartner's Magic Quadrant for Enterprise Information Archiving (EIA) based on both the quality of its flagship offering and its unwavering commitment to customer satisfaction. ZL's history, vision, and commitment to attracting and retaining the highest caliber of talent ensure that Unified Archive will be the go-to information governance solution—for Fortune 500 companies and public sector agencies with high data volumes alike—for years to come.
Scott Amyx's book "Strive" shows how you can shape your life and your career, a life of fulfillment and joy, constantly creative and productive, one that always holds the possibility of delightful surprise.
Amyx Ventures is an industry building-venture fund specific to countries and economic regions with its strategy pillared on incubating new transformational industries. The fund creates advanced IPs, develops technologies around those IPs, validates the business models and products with the market, and then launches startups when there are sufficient evidence of market fit and adoption.
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.
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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!
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