If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Identifying different foods on a tray can be a non-trivial task (Image source: Chris A. Tweten on Unsplash) Unfortunately, we don't always have sufficient time to enjoy a leisurely lunchtime meal. Suppose some of your workmates invite you to join them for lunch at a local fast-food restaurant. You all typically have a limited amount of time for your lunchtime break and you need to use this time wisely and efficiently. First, you have to get to the restaurant, either by walking or perhaps by taking a short drive. When you reach the restaurant, you have to select your food, pay for it, and eat it.
Dr. Albert Hsiao and his colleagues at the University of California–San Diego health system had been working for 18 months on an artificial intelligence program designed to help doctors identify pneumonia on a chest X-ray. When the coronavirus hit the United States, they decided to see what it could do. The researchers quickly deployed the application, which dots X-ray images with spots of color where there may be lung damage or other signs of pneumonia. It has now been applied to more than 6,000 chest X-rays, and it's providing some value in diagnosis, said Hsiao, the director of UCSD's augmented imaging and artificial intelligence data analytics laboratory. His team is one of several around the country that has pushed AI programs developed in a calmer time into the COVID-19 crisis to perform tasks like deciding which patients face the greatest risk of complications and which can be safely channeled into lower-intensity care.
Data scientists come from different backgrounds. In today's agile environment, it is highly essential to respond quickly to customer needs and deliver value. Faster value provides more wins for the customer and hence more wins for the organization. Information Technology is always under immense pressure to increase agility and speed up delivery of new functionality to the business. A particular point of pressure is the deployment of new or enhanced application code at the frequency and immediacy demanded by typical digital transformation.
One of the foundations of the bio revolution now underway is the knowledge base was built over 13 years as scientists mapped the human genome. However, the power of that map to fuel innovation only materialized when it became cheaper and quicker to sequence DNA because of advances in computing. Today, the cost of DNA sequencing is decreasing at a rate faster than Moore's Law. In 2003, mapping the genome cost about $3 billion; by 2016, that had dropped to less than $1,000 and could be less than $100 in less than a decade. Scientists sequenced the coronavirus responsible for COVID-19 in weeks rather than the months it took to sequence the virus responsible for the original SARS epidemic.
The automation wave has overtaken IT departments everywhere making DevOps a critical piece of infrastructure technology. DevOps breeds efficiency through automating software delivery and allowing companies to push software to market faster while releasing a more reliable product. What is next for DevOps? We need to look no further than artificial intelligence and machine learning. Most organizations quickly realize the promise of AI and machine learning, but often fail to understand how they can properly harness them to improve their systems.
The artificial intelligence model showed great promise in predicting which patients treated in U.S. Veterans Affairs hospitals would experience a sudden decline in kidney function. But it also came with a crucial caveat: Women represented only about 6% of the patients whose data were used to train the algorithm, and it performed worse when tested on women. The shortcomings of that high-profile algorithm, built by the Google sister company DeepMind, highlight a problem that machine learning researchers working in medicine are increasingly worried about. And it's an issue that may be more pervasive -- and more insidious -- than experts previously realized, new research suggests. The study, led by researchers in Argentina and published Monday in the journal PNAS, found that when female patients were excluded from or significantly underrepresented in the training data used to develop a machine learning model, the algorithm performed worse in diagnosing them when tested across across a wide range of medical conditions affecting the chest area.
Ambarella's products are used in a wide variety of human and computer vision applications, including video security, advanced driver assistance systems (ADAS), electronic mirror, drive recorder, driver/cabin monitoring, autonomous driving and robotic applications. Per a recent evaluation, an Ambarella computer vision (CV) system on chip (SoC) and PCB were run on the Cadence Clarity 3D Solver. Results of both simulations show that when there is no solid reference plane for high-speed signals, the Clarity 3D Solver identifies the Ambarella design defects and correct scattering parameter (S-parameter) response. For both simulations, the Clarity 3D Solver, a 3D electromagnetic solver using 32 CPUs, took just 29 hours to process the case with 202 ports running at 48 bits via a LPDDR4 interface on a geometrical combination of package and PCB layout design. "Ambarella continuously upgrades our system design methodologies to stay ahead of the competition," said Chan Lee, vice president of VLSI at Ambarella, Inc. "The speed, capacity and accuracy of the Cadence Clarity 3D Solver enable us to accelerate our design process and shorten our schedule. We expect that many of the likely challenges of our next-generation 5nm AI design project can be easily and quickly addressed with the Cadence Clarity 3D Solver."
IIT-Ropar, one of the eight new IITs established by the Ministry of Human Resource Development (MHRD), Government of India, and TSW, the executive education division of Times Professional Learning (a part of The Times of India Group), have launched a Post Graduate Certificate Programme in Artificial Intelligence & Deep Learning. The programme will be coordinated by The Indo-Taiwan Joint Research Centre (ITJRC) on Artificial Intelligence (AI) and Machine Learning (ML), at IIT-Ropar. Supported by the Ministry of Science and Technology, Taiwan, ITJRC is a bilateral centre for collaborative research in disruptive technologies like AI and ML. The programme, with its focus on Artificial Intelligence and Deep Learning, has an eligibility criterion of a minimum of 2 years of work experience in the IT industry. Though an engineering degree is a desirable prerequisite for this programme, one does not need a coding or mathematics background to be eligible.
An important problem faced by auditors is gauging how much reliance can be placed on the accounting systems that process millions of transactions to produce the numbers summarized in a company's financial statements. Accounting sys-ems contain internal controls, procedures designed to detect and correct errors and irregularities that can occur in the processing of transactions. In a complex accounting system, it can be an extremely difficult task for the auditor to anticipate the possible errors that can occur and evaluate the effectiveness of the controls at detecting them. An accurate analysis must take into account the unique features of each company's business processes. To cope with this complexity and variability, the COMET system applies a model-based reasoning approach to the analysis of accounting systems and their controls.
Language processing has a large practical potential in intelligent interfaces if we take into account multiple modalities of communication. Multi-modality refers to the perception of different coordinated media used in delivering a message as well as the combination of various attitudes in relation to communication. In particular, the integration of natural language processing and hypermedia allows each modality to overcome the constraints of the other, resulting in a novel class of integrated environments for complex exploration and information access. Information presentation is a key element of such environments; generation techniques can contribute to their quality by producing texts ex novo or flexibly adapting existing material to the current situation. A great opportunity arises for intelligent interfaces and language technology of this kind to play an important role for individual-oriented cultural tourism.