In part 3 of this deep tech series we delve into projects that achieved success and have remained relevant through the recent years
For the last two weeks we have been covering how the deep tech mentality has not only changed the way innovators and entrepreneurs envision their startups, but also caught the attention of investors and has overtaken the competition in nearly every field of technology thanks to its problem-oriented focus, the cyclic nature of its design and development process, and the tendency towards filing patents for the developed technologies, ensuring exclusivity and market presence.
For this final part, we will cover a number of projects that achieved success and have remained relevant through the recent years, along with other promising startups that may take the first steps in the next innovation era of their respective fields.
Arguably the field where the problem-solving cycle of deep tech shows the best result, AI benefits greatly for the iteration-based mentality as problems and issues are fixed over time, while the validation algorithms are tuned continuously.
The big first example of artificial intelligence projects based on deep tech is OpenAI, a research lab focused on understanding Artificial General Intelligence (AGI) for human safety. AGI is defined as the next step beyond AI, since machines could be able to successfully learn and perform intellectual tasks, which has led them to pave the way in associated fields like Machine Learning, and extraction and handling of relevant sets of Big Data.
While some projects focus on developing AI systems that can be applied to final products, others also aim to create AI-based tools that can be of use during earlier R&D stages, which is the case with Noble.AI. Founded in 2017, Noble.AI is a software company based in California focused on creating scalable technologies for the sectors of R&D and scientific research, providing organizations with tools that can fulfill their requirements while reducing both times and costs. Their portfolio includes two Software-as-a-Service platforms:
Blueprint, a platform that is able to extract information from a wide variety of numeric, graphic, simulated, and textual sources, and provide insight on trends or errors found within the database.
Reactor, a software that allows users to acquire relevant data from experiments in the fields of chemistry, materials science, energy, electronic systems, aerospace and more, in order to get better insight on the results and reaching deeper insights.
Healthcare and Biomedicine
The field of healthcare, biomedical and pharmaceutic research saw a great benefit in the popularization of deep tech, and it becomes easily noticeable when compared to projects developed with the mentality of the previous wave of innovation. Problem-oriented startups find fertile ground in deep tech thanks to the reduced R&D times and the reduced market risk associated to the release of a product (if a problem already exists, the solution already has a target market).
The most recent example of this dynamic comes from Covaxx, a company that not only led the charge in the development of quick, reliable tests for detection of COVID-19, effectively improving the response of multiple governments by helping in the quantification of the scale of the pandemic, but also later entering in the vaccine developing market and reaching a solution with no significant safety issues observed to date, rapid adaption to mutations, no need for specialized cold-chains and already reaching projected production rates of 500 million doses per year.
Projects in different fields of medicine have also gained traction by the hand of familiar names showing their public support, like Stephen Hawking’s recognition for Medcura (former Gel-e) and their innovative design of bleeding control mechanisms. With multiple FDA-approved products and more in development, Medcura’s vision to create solutions to prevent bleeding, maintaining the wounds clean, and enhancing the clotting cascade makes them shine in a wide market that covers from regular household incidents to military deployments.
Transportation and Energy
Dating even further than medicine and pharmaceutics, the fields of transportation and energy have seen constant improvements over multiple centuries and are living records of the discoveries and advancements made during several industrial revolutions and seem to be having difficult times in innovation due to massive corporate involvement.
In Part I, we covered how Commonwealth Fusion Systems, a Boston-based startup, is currently competing and expecting to overperform efforts to implement nuclear fusion reactors by coalitions of multiple countries, and with an earlier expected launch date. But there are more examples in the field of energy generation, of which we highlight Heliogen, a company that focuses on concentrated solar power solutions aiming to shift the standard from fossil fuels to renewable sources, utilizing advanced computer vision software to precisely align mirrors to focus the energy on a single target to make use of larger amounts of energy.
The shift from fossil fuels has also permeated to transportation, where Tesla has led the charge in the popularization of electric and semi-autonomous vehicles by not only streamlining their manufacturing and availability to the public, but also creating a friendly landscape for its adoption by offering solutions of charging and maintenance. By the hand of the eccentric management of Elon Musk, the American manufacturing company has taken the world by storm and remains the flagship of Musk’s incredibly wide range of projects that include reusable spacecrafts, ultra-high-speed transport by tunnels and even computer-brain integration solutions.
To deny the influence that the deep tech mentality has had and will continue to have in nearly every field of industry and technology is to fall behind as more daring and creative startups gain experience, market presence and financial support, leading them to the top spots in fields considered to be of extreme relevance today and to have nearly unlimited potential for the following decades. The best solution is to take an introspective look at how we think not only as individuals, but as parts of a systems that currently craves for innovation and that, as seen in this series, is willing to take risks in exchange to be the early bird that catches the worm.
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