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.
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.
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).
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.
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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