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Memoization in Python: The Essence of Dynamic Programming

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Dynamic programming is a method developed by Richard Bellman in 1950s. The main idea behind the dynamic programming is to break a complicated problem into smaller sub-problems in a recursive manner. In computer science and programming, the dynamic programming method is used to solve some optimization problems. The dynamic programming is a general concept and not special to a particular programming language. But, we will do the examples in Python.


Machine learning approach could improve radar in congested environments - Military Embedded Systems

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Research being conducted by the U.S. Army Combat Capabilities Development Command (DEVCOM) is focused on a new machine learning approach that could improve radar performance in congested environments. Researchers from DEVCOM, Army Research Laboratory, and Virginia Tech have developed an automatic way for radars to operate in congested and limited-spectrum environments created by commercial 4G LTE and future 5G communications systems. The researchers claim they examined how future Department of Defense radar systems will share the spectrum with commercial communications systems. The team used machine learning to learn the behavior of ever-changing interference in the spectrum and find clean spectrum to maximize the radar performance. Once clean spectrum is identified, waveforms can be modified to best fit into the spectrum.


Autonomous a2z Raises US$1.9M in Seed Round for Autonomous Driving Solution

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Autonomous a2z, a member company of Born2Global Centre and Sejong Technopark, has recently received a seed investment of US$1.9 million from angel investments by individuals and partner corporations. Autonomous a2z is a company specializing in autonomous mobility solutions. The startup announced that it has begun commercializing an ongoing project. It also stated that the infusion of capital is already serving as a stepping stone for future development of autonomous mobility solutions and for assuming a leading position in relevant markets. Founded in 2018, Autonomous a2z has advanced its cutting-edge technologies to test self-driving technologies throughout Korea. As implied by its name, the firm develops "everything from a to z" in the arena of self-driving cars, including its own systems and algorithms.



Using AI to drive success along the customer lifecycle yields big returns

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Artificial intelligence technologies are now so advanced that even facets of technology like sentiment analysis, cutting edge in 2010, have been …


Pentagon Teams with Howard University to Steer Artificial Intelligence Center of Excellence

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The work will hone in on military-centered machine learning application development, research into trustworthy AI tech--and could help boost DoD's …



Creator Of Amazon's Zoox Robotaxi Unit Has A New Self-Driving Startup

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HYPR is testing its self-learning autonomous driving system in a modified Daimler Smart Car. As Zoox, the secretive robotaxi developer recently acquired by Amazon, gets ready to unveil its futuristic fleet vehicle, its former CEO who dreamed up the company is re-emerging with a new startup that's designing AI-enabled software he hopes will allow cars to "teach themselves" to drive. Early-stage HYPR, created by Zoox cofounder Tim Kentley Klay, says it's using reinforcement learning, a branch of machine learning that utilizes a reward-based approach, to train driving algorithms dynamically–ideally with no need for direct human instruction or supervision. The Alameda, California-based startup has raised a $10 million seed round and begun testing its approach with a modified Daimler Smart Car. Backers include R7 Ventures and Australian billionaire Andrew Forrest.


Human and Artificial Intelligence Merge

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… which announced the most recent advance, hailed the achievement as another step toward the merger of the human brain and artificial intelligence, …


Google's AI taps into the minds of the great poets

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"I need about one hundred fifty drafts of a poem to get it right, and fifty more to make it sound spontaneous." So said the 1966 U.S. Poet Laureate James Dickey. One could only imagine how Dickey would react today if he had Google's latest AI project Verse by Verse by his side. He could whip out 150 drafts in minutes with 150 mere clicks of a key, and with those 50 additional clicks, sculpt his initial passages into the grandest styles of any of dozens of his literary peers. For all aspiring great poets today--and for all those whose poems simply suck--there is help.