Tag: machine learning

Artificial Intelligence: Simply Complex

by on July 20, 2018 8:38 am
I believe that, in science, holding a simplistic view regarding a problem or a technology is risky and potentially misleading to others. In the same way, overcomplicating the challenges behind a given problem or fantasizing about the capabilities of the corresponding solution is, typically, a sign of incomprehension and lack of expertise. Interestingly enough, artificial… Read more Artificial Intelligence: Simply Complex

Artificial Intelligence (ANI & AGI) and its impact on society

by on July 20, 2018 4:13 am
Recent advancements in AI/ML are mainly due to improvements in processor technologies and cloud data. AI primarily consists of methods that enable computers to mimic human intelligence using logic, if-then rules, decision trees, and machine learning (including deep learning).[1] Deep learning – a subset of machine learning – contains algorithms that permit software to train… Read more Artificial Intelligence (ANI & AGI) and its impact on society

Artificial Intelligence, Cloud, Mobile Devices and Networks

by on July 19, 2018 11:16 pm
A key takeaway from Jeff Welser’s (Vice President and Lab Director, IBM Research) presentation is that we are creating data at twice the speed than bandwidth in our networks. Large parts of Big Data Analytics and Artificial Intelligence (AI) products and services today have been built using the resources of cloud computing. According to  Craig Martell… Read more Artificial Intelligence, Cloud, Mobile Devices and Networks

Military Drone latencies

by on July 19, 2018 7:32 pm
The near future in the aviation industry looks to be one hundred percent autonomous. There are already current military systems that are able to control and navigate autonomous systems from nearby bases and unmanned aerial vehicles that possess the power to access remote areas to conduct search operations, deliver potential packages, supply raw materials, scan earth… Read more Military Drone latencies

Hic Sunt Dracones

by on July 19, 2018 4:32 pm
The Space Race started with an early lead by the Soviet Union, which managed to reach a stable orbit with the first ever artificial satellite, the Sputnik 1. This impressive achievement started the so-called “Sputnik Crisis” in the United States, as the West feared that the USSR had surpassed it in space-related technologies, which had obvious… Read more Hic Sunt Dracones

Detecting Phishing on the "Edge"

by on July 19, 2018 9:38 am
Last week I talked about how building software in 2004 was different than in 2018 in the context of an anti-phishing startup I co-founded at that time. This week I want to dive deeper into how we used machine learning. According to Craig Martell, head of a data science group at Linked In, the goal of… Read more Detecting Phishing on the "Edge"

Why Siri sucks (and will continue to suck)

by on July 18, 2018 2:18 pm
In class we discussed trends in AI, and had some incredible speakers who diffused several myths.  In this blog, I will take on why Siri….. well…. sucks. Some critics think that Apple is too large, and thus is not able to innovate new products and services. The notoriously lagging performance of Siri is a perfect example… Read more Why Siri sucks (and will continue to suck)

Neural Networks - Garbage in, garbage out

by on July 15, 2018 10:52 pm
I came across this article and I am somewhat concerned about how much we are potentially relying on neural nets and their “supposed” efficacy. https://physicsworld.com/a/neural-networks-explained/ 0

Evolution of Compute and Big data

by on July 15, 2018 12:57 pm
The primitive cloud, better known as “virtualization” evolved as a way to abstract the physical infrastructure which used to be manually deployed. The evolution of cloud computing from plain server virtualization is depicted in the flow below developed by Gartner in 2012 [1]. The first big step in compute evolution was from physical servers to… Read more Evolution of Compute and Big data

Impact of machine learning in manufacturing in recent times

by on July 13, 2018 7:46 pm
Improving semiconductor manufacturing yields up to 30%, reducing scrap rates, and optimizing fab operations are is achievable with machine learning. Attaining up to a 30% reduction in yield detraction in semiconductor manufacturing, reducing scrap rates based on machine learning-based root-cause analysis and reducing testing costs using AI optimization are the top three areas where machine learning… Read more Impact of machine learning in manufacturing in recent times