I continue to think that Robots are the next big technology trend. The COVID-19 event seems to make this even more likely because of the need to keep people apart from each other to prevent the virus’ spread.
This week Qualcomm put on a presentation on this topic with their focus being on 5G connecting these robots to centralized AI resources. This presentation was designed to showcase their Robotics RB5 platform but is also showcased a different way to create robots so that they are more reliable, smarter, and less expensive to build. Read More
Daily Archives: July 16, 2020
Deepfake used to attack activist couple shows new disinformation frontier
Oliver Taylor, a student at England’s University of Birmingham, is a twenty-something with brown eyes, light stubble, and a slightly stiff smile.
Online profiles describe him as a coffee lover and politics junkie who was raised in a traditional Jewish home. His half dozen freelance editorials and blog posts reveal an active interest in anti-Semitism and Jewish affairs, with bylines in the Jerusalem Post and the Times of Israel.
The catch? Oliver Taylor seems to be an elaborate fiction. Read More
The great acceleration
The fault lines between industries and business models that we understood intellectually before the COVID-19 crisis have now become giant fissures, separating the old reality from the new one. Just as an earthquake produces a sudden release of pent-up force, the economic shock set off by the pandemic has accelerated and intensified trends that were already underway. The result is a dramatic widening of the gap between those at the top and the bottom of the power curve of economic profit 1 —the winners and losers in the global corporate-performance race. Read More
Google’s quiet experiments may lead to smart tattoos, holographic glasses
A simple pair of sunglasses that projects holographic icons. A smartwatch that has a digital screen but analog hands. A temporary tattoo that, when applied to your skin, transforms your body into a living touchpad. A virtual reality controller that lets you pick up objects in digital worlds and feel their weight as you swing them around. Those are some of the projects Google has quietly been developing or funding, according to white papers and demo videos, in an effort to create the next generation of wearable technology devices. Read More
Is Artificial General Intelligence (AGI) On The Horizon? Interview With Dr. Ben Goertzel, CEO & Founder, SingularityNET Foundation
The ultimate vision of artificial intelligence are systems that can handle the wide range of cognitive tasks that humans can. The idea of a single, general intelligence is referred to as Artificial General Intelligence (AGI), which encopmasses the idea of a single, generally intelligent system that can act and think much like humans. However, we have not yet achieved this concept of the generally intelligent system and as such, current AI applications are only capable of narrow applications of AI such as recognition systems, hyperpersonaliztion tools and recommendation systems, and even autonomous vehicles. This raises the question: Is AGI really around the corner, or are we chasing an elusive goal that we may never realize? Read More
What is adversarial machine learning?
This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI.
To human observers, the following two images are identical. But researchers at Google showed in 2015 that a popular object detection algorithm classified the left image as “panda” and the right one as “gibbon.” And oddly enough, it had more confidence in the gibbon image. Read More
Headline Generation: Learning from Decomposable Document Titles
We propose a novel method for generating titles for unstructured text documents. We reframe the problem as a sequential question-answering task. A deep neural network is trained on document-title pairs with decomposable titles, meaning that the vocabulary of the title is a subset of the vocabulary of the document. To train the model we use a corpus of millions of publicly available document-title pairs: news articles and headlines. We present the results of a randomized double-blind trial in which subjects were unaware of which titles were human or machine-generated. When trained on approximately 1.5 million news articles, the model generates headlines that humans judge to be as good or better than the original human-written headlines in the majority of cases. Read More
Image Search with Text Feedback by Visiolinguistic Attention Learning
Image search with text feedback has promising impacts in various real-world applications, such as e-commerce and internet search. Given a reference image and text feedback from user, the goal is to retrieve images that not only resemble the input image, but also change certain aspects in accordance with the given text. This is a challenging task as it requires the synergistic understanding of both image and text. In this work, we tackle this task by a novel Visiolinguistic Attention Learning (VAL) framework. Specifically, we propose a composite transformer that can be seamlessly plugged in a CNN to selectively preserve and transform the visual features conditioned on language semantics. By inserting multiple composite transformers at varying depths,VAL is incentive to encapsulate the multi-granular visiolinguistic information, thus yielding an expressive representation for effective image search. We conduct comprehensive evaluation on three datasets: Fashion200k, Shoes and FashionIQ. Extensive experiments show our model exceedsexisting approaches on all datasets, demonstrating consistent superiority in coping with various text feedbacks, including attribute-like and natural language descriptions. Read More
Rick's Cafe AI 