Skip to main content

Featured Post

We Should Have Already Had This: The Lithium-Ion Battery With Built-In Fire Suppression

On October 22, 2020, yesterday, Dexter Johnson posted The Lithium-Ion Battery With Built-In Fire Suppression. Within this topic, Dexter Johnson regards a Stanford University research team and the SLAC National Accelerator Laboratory (its former name was the Stanford Linear Accelerator Center[1]). Johnson stated:Now [Yi] Cui and his research team, in collaboration with SLAC National Accelerator Laboratory, have offered some exciting new capabilities for lithium-ion batteries based around a new polymer material they are using in the current collectors for them. The researchers claim this new design to current collectors increases efficiency in Li-ion batteries and reduces the risk of fires associated with these batteries.[2]Johnson was saying this: fires are a current Li-ion battery threat that has been realized, but a new design can secure client use-case safety, and this required this battery redesigned. As this technology approaches marketplace entry points, this shall confront Li-io…

On Neuromorphic Chips: Advanced AI, Deep Learning, and Neural Network Computer Architecture

Neuromorphic Chips to Become Affordable


In the August 2020 edition of Communications of the ACM, West Linn, OR, USA-based author and journalist, Samuel Greengard, wrote Neuromorphic Chips Take Shape. The available data Greengard had is the claim that a Caltech (The California Institute of Technology) professor invented this technology, neuromorphic chips. Greengard wrote, “The concept of a brain-like computing architecture, conceived in the late 1980s by California Institute of Technology professor Carver Mead, is suddenly taking shape” (Greengard, Aug 2020, p. 9). Since the date, today, is around forty years later, this technology has remained dormant, but not in the research, thus so recent advancements probably allowed neuromorphic chips to become affordable (With LTE capabilities, see current pricing of a standard productivity PC, an i5 Microsoft Surface Pro: (link). With 3G capabilities, alternatively see the current pricing of a legacy, but GPU intensive PlayStation Vita: (link)).

Safely Surpassing the von Neumann Bottleneck


With maximum efficiency regarded, Greengard mentioned that this contentious model is aiming against the ineffective von Neumann bottleneck: this demands a processor enter an idle state, but it awaits memory data (see a fast external SSD: link) or other component data inclusively moving; however, this is an intense computation, and it plateaus exponentially worse problems. These exponentially worsening problems not inclusively are AI (see 2001: A Space Odyssey, a popular film regarding advanced data technologies including artificial intelligence: link), so thus this is a deep learning issue addition, but machine learning is also remaining a power-intensive issue, unfortunately.


This May be the Next Crucial Step Data Science Demands to Survive

On Greengard’s column, Chris Eliasmith, a Systems Design Engineering and Philosophy professor of the University of Waterloo located in Ontario, Canada, stated neuromorphic parallelism is a refreshing standard (see a book on parallelism because I read this as an undergraduate, but I do not recommend any particular book: link). Greengard wrote that Eliasmith said, “Neuromorphic chips introduce a level of parallelism that doesn’t exist in today’s hardware, including GPUs and most AI accelerators” (Greengard, Aug 2020, p. 9). According to Greengard, contemporary deep learning systems are dependent against software measurements to play oversimplified neuromorphic systems: they use standardized FPGAs (On field-programmable gate arrays, see this computer organization architecture book that I read because I was an undergraduate Computer Science major: link), CPUs (on Central Processing Units, see this text (this is the same Computer Organization and Architecture book): link), and GPUs (On Graphics Processing Units, see this text: link). As Greengard mentions, this technology as a single deliverable chip might be as effective as researchers have begun developing: touch-sensing prosthetics, anti-stroke or anti-Alzheimer’s brain implants, or self-healing electronic skin; or vision technology...other possibilities are predicting an earthquake or, I believe, an economic recession. According to Greengard, this technology shall be knowable as an embedded processor during the next year or two years on commercial markets.

With no many any longer populating the Garden of Eden, invest in Mental Stability.

In Scripture (NIV: link), there is a record of Adam being taken by ABBA, but then Adam being put in the Garden of Eden: Genesis 2:15. With that event done, then Adam and Eve were driven from the Garden of Eden (Genesis 3:24), investments became a recurring long-term proof that persons were willing to work. In the time of the Ecclesiates being written, this was probably proven by Solomon, kinsman of David, who invested in wisdom literature (Ecclesiastes 1:1), but this was a condemnation of Solomon because Solomon married seven hundred women and had his ways with three hundred concubines, worshipping himself through fertility rituals foreign to Israel (1 Kings 11). However, for others, Biblical wisdom literature has remained relevant over the generations since Solomon passed away because of this: mental illness doctrine like the APA’s (American Psychological Association) has remained unscientific to this day. The unscientific part was recorded in Genesis because Adam died for eating the fruit of the tree of knowledge of good and evil (Genesis 5:5), but more recently, in the APA’s case, not having a biological standard for typical or atypical antipsychotic medications, the related law enforcement conduct, and the court cases surrounding them then the culture supporting this entity. I wish Greengard or anyone he cited would have expressed interest for investing in R & D (see this Software Engineering text because the first phase of a Software Engineering project ought to involve Research and Development as project management does: link)  programming regarding the applicability of neuromorphic chips on mental illness cases, but none did, here. Hopefully, by the time neuromorphic chips are on the market, this shall come to pass, or maybe I shall have this opportunity, myself. 

A Smart phone is serving as a technology hub.
Image by Gerd Altmann from Pixabay

References

Greengard, S. (2020). Neuromorphic chips take shape. Communications of the ACM, 63(8), 9-11. doi:10.1145/3403960



Comments

Popular posts from this blog

In response to the Institute of Industrial Science, the University of Tokyo’s Circular Reasoning: Spiral Circuits for More Efficient AI

Circular Reasoning
On June 14, 2020, the IIS (Institute of Industrial Science) at the UTokyo (University of Tokyo) wrote Circular Reasoning: Spiraling Circuits for More Efficient AI; but a Press Release from this institute is giving a synopsis on this topic. On this press release, the IIS wrote, “Researchers from the Institute of Industrial Science at the University of Tokyo designed and built specialized computer hardware consisting of stacks of memory modules arranged in a 3D-spiral for artificial intelligence (AI) applications” (IIS, June 14, 2020). The IIS continued on, saying this research is allowing a singular way work can be done regarding the next generation energy efficient AI devices (Here is a current generation, but energy efficient, AI device, Android Pie: link) shall be implemented into production.            The Fundamentals of Machine LearningOn this press release, the IIS is explaining the fundamentals of ML (Machine Learning). The IIS wrote, “Machine learning is a ty…

IS the Future of AI “Women?”

Interdisciplinary Campus Culture
On April 14, 2020, Katy Rank Lev wrote the Carnegie Mellon University’s (CMU) news article The Future of AI is Female. Since artificial intelligence’s (AI) initial measurement, wrote Lev, CMU built AI. Lev wrote that each of the colleges CMU is representing contribute to make AI a new field, describing this AI as a frontier, humanity can democratize: from healthcare, the eventual goal area is education. In a rush, Lev cut the conversation short, and Lev mentioned CMU’s interdisciplinary campus culture as the source of the effective AI women, but this is despite women historically not represented as scientists, technologists, and engineers, and math (STEM), worldwide. But CMU is spotlighting undergraduate students and highly honored faculty members, and Lev is including these women because she agrees with the Women in Tech movement as far as the East is from the West: CMU is the best Computer Science University with AI, and this is IT at this point in ti…

Drone Uses AI and 11,500 Crashes to Learn How to Fly

Learning to Fly by Crashing
On 10 May, 2017, Evan Ackerman wrote the IEEE (Institute for Electricians and Electrical Engineers) SPECTRUM article Drone Uses AI and 11,500 Crashes to Learn How to Fly. In Ackerman’s article, Ackerman used a block quote by Carnegie Mellon University roboticists Dhiraj Gandhi, Lerrel Pinto; and Abhinav Gupta, the writers of a paper, “Learning to Fly by Crashing” (Gandhi, et. al., 27 Apr 2017). From Ackerman’s block quote from Gandhi, et. al., “[T]he gap between simulation and real world remains large especially for perception problems” (Gandhi, et. al.). Ackerman contrasted known motion from unconfirmed motion without identifying the pre-existing condition called Schrödinger’s cat in the case that the crashes shall eventually happen without outside help: a continuing crash failure, and in security terms this is interned as a false positive because this helps Schrödinger’s cat stay alive or rest buried in the soil. In this case, this drone detects these two …

Contact Form

Name

Email *

Message *