Category Archives: Artificial Intelligence
Who’s leading the way? Top ranked mining companies in the artificial intelligence theme – Mining Technology
The future of the mining industry will be shaped by a range of disruptive themes, with artificial intelligence (AI) one of the themes that will have a significant impact on mining companies.
The mining industry is under more pressure than ever to increase efficiencies. This comes as declining ore grades and more disparate and remote deposits create greater challenges in securing new resources, and rising mining costs drive the need for greater productivity at the mine site. At the same time, there is a strong focus on ensuring safety and sustainability within mines. Artificial intelligence (AI) can address many of these challenges and inefficiencies through several key technologies in the value chain, including computer vision, smart robots, data science, and machine learning.
Exploration costs can be reduced by using AI to identify the most likely locations of mineral deposits. Predictive maintenance can ensure that equipment defects are solved before they become extremely costly and ensure that equipment downtime is kept to a minimum, increasing productivity. Smart sensors and cameras aid automated equipment while also monitoring the safety of workers in mines.
However, not all companies are equal when it comes to their capabilities and investments in the key themes that matter most to their industry. Understanding how companies are positioned and ranked in the most important themes can be a key leading indicator of their future earnings potential and relative competitive position.
According to GlobalDatas thematic research report, Artificial Intelligence (AI) in Mining, leading adopters include: Goldcorp, BHP, Rio Tinto, Freeport-McMoRan, Fortescue Metals Group, Newcrest, Barrick Gold, Dundee Precious Metals
BHP
BHPs Maintenance Centre of Excellence performs ML on vast troves of data collected from its operational equipment. This provides actionable insights for predictive maintenance on items such as haul trucks and improving supply chain management. The company also employs self-driving trucks to reduce accidents caused by fatigued drivers and automated drills. BHP fortified its supply chain during the COVID-19 pandemic using analytics. At its 2019 SmartMine conference, the company demonstrated its use of ML to interpret geological data and generate targets.
The company also currently has the largest fleet of autonomous trucks in operation with 300 spread across ten mines. The company has invested evenly across Komatsu and Caterpillar with a recent investment at South Flank with 42 Komatsu 930E ATs. It has operated a fully-autonomous truck fleet at its Jimblebar mine in Western Australia since 2017 and has cited benefits such as productivity increases of 20%, operating cost reduction of 20% and over 90% reduction in haul accidents due to the automation of trucks.
Rio Tinto
Rio Tinto has been incorporating automation into its operations for more than a decade to improve safety, efficiency, and reduce the cost of operations. Automated trucks, drills, and trains are used to remove driver error, thus improving safety. Rio Tinto is closing the gap on BHP the opening of its Gudai-Darri iron ore mine will add 23 CAT 793F autonomous haul trucks to its total taking it to 210, which would move it into second place ahead of Fortescue Metals Group.
The companys Iron Ore business operates AutoHaul, the worlds first fully autonomous heavy-haul long-distance railway system. AutoHaul transports iron ore to port facilities in the Pilbara region of Western Australia. Around 200 locomotives on more than 1,700km of track have travelled over 7 million km to date. Each 240-wagon hauler is 2.4km long, requiring two to three locomotives to transport 28,000 tonnes of iron ore, an average of 800km over 40 hours. Using this autonomous technology reduces risk at level crossings and auto-responds to speed restrictions and alarms, improving overall safety. By eliminating the need to transport drivers to and from trains mid-journey, almost 1.5 million km of road travel are saved annually. This also removes the need to change drivers two to three times during the journey, saving an hour from each journey and increasing average speeds by between 5 and 6%. AutoHaul can move about one million tons of iron ore a day. Loading and unloading product from the wagons is an entirely automated process.
Fortescue Metals Group
Fortescue has undertaken one of the largest fleet conversions to autonomous haulage projects, with almost 200 autonomous trucks operating at its Solomon and Chichester hubs. The fleet includes Cat 793F, 789D, and Komatsu 930E haul trucks. Since 2013, the fleet has safely travelled over 52 million km and moved 1.5bn tons of material. Some 900 additional assets, such as excavators, wheel loaders, and light vehicles, are integrated with the autonomous fleet using CAT Minestar Command for Hauling Technology. Fortescues autonomous haulage fleet has delivered a 30% increase in productivity. Fortescue plans to use the data collected from the autonomous haulage fleet to understand their operations better and look for ways to optimize, such as haul road design and maintenance scheduling.
Sources
GlobalData, the leading provider of industry intelligence, is the parent company of Mining Technology and provided the underlying data, research, and analysis used to produce this article.
GlobalDatas Thematic Scorecard ranks companies within a sector based on their overall leadership in the 10 themes that matter most to their industry, generating a leading indicator of their future earnings and relative position within key strategic areas.
Drill and Blast Solutions for Open-Pit and Underground Mining Applications
Mohamed bin Zayed University of Artificial Intelligence Advances the UAE’s National Strategy for AI with New Supercomputer Built by Hewlett Packard…
DUBAI, United Arab Emirates--(BUSINESS WIRE)--Hewlett Packard Enterprise (NYSE: HPE) today announced it is building a new supercomputer for Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), a university dedicated solely to AI, to accelerate AI-driven scientific discovery and advance the UAEs goal to be a global AI leader. HPEs robust supercomputing and AI technologies will significantly enhance the universitys ability to run complex AI models with extremely large data sets, and increase predictability in research analyses in fields including energy, transportation and the environment.
Supercomputing is vital to delivering AI-at-scale, and driving global innovation, industry competitiveness, and economic growth. From accelerating vaccine discovery to fight a pandemic, and advancing clean energy systems to increase sustainability, to enabling new possibilities in AI, supercomputing is a core technology to solving the worlds most challenging scientific and engineering challenges.
Established in 2019, MBZUAI has already ranked 24th in the world for artificial intelligence, computer vision, machine learning, and natural language processing. The new supercomputer will help MBZUAI support the UAEs National Strategy for AI, bringing together the power of academia, government, and industry to strengthen the countrys global competitiveness. The advanced supercomputing and AI technologies will also expand resources for larger projects to allow MBZUAI to attract global talent and create new economic and societal opportunities for the UAE.
MBZUAIs new Campus Super Computing Center (CSCC), where the new supercomputer will be housed, will enable faculty members, researchers, and students to accelerate scientific discovery in many areas, including healthcare, structural engineering, law enforcement, supply chain, and sustainability. In addition to meeting the research needs of the faculty and students, the new supercomputer will help MBZUAI fulfill its role as an AI talent developer and innovation hub that brings together the business community to drive entrepreneurship in the AI sector. MBZUAI already is contributing to significant initiatives such as the Emirati Genome Program, which uses AI-based tools to extract and interpret large amounts of complex data resulting from DNA sequencing, and the Abu Dhabi Health Services Company, SEHA, which uses AI algorithms to predict heart attacks.
Supercomputing plays an essential role in unleashing AI to achieve significant breakthroughs for organizations worldwide, across public and private sectors, said Justin Hotard, executive vice president and general manager, HPC, AI & Labs, at HPE. HPE is leading the market in this next frontier by combining supercomputing performance and capabilities with solutions that are purpose-built for AI, to build and train machine learning models at-scale. MBZUAIs Campus Super Computing Center is demonstrating this capability to unlock new possibilities in AI and strengthen UAEs position as an AI-driven nation to advance key initiatives in healthcare, sustainability, and engineering.
HPE has a longstanding commitment to advancing the way people live and work in the United Arab Emirates, through our Emiratization program, Digital Life Garage, and industry and government partnerships, said Ahmad Alkhallafi, managing director for UAE, Hewlett Packard Enterprise. We are proud to support the UAEs national strategy for AI by helping MBZUAI grow its contribution to research and education. Supercomputing will play a crucial role in helping the UAE anticipate and take advantage of new AI technologies now and in the future. We look forward to helping the UAE meet its goal to be an AI leader by 2031.
As a recently established institution, MBZUAI is still building its team of in-house supercomputing specialists. By collaborating with HPE, the university is gaining access to a large local team for supercomputing and AI support, in addition to world-leading technologies.
The new supercomputer will deliver end-to-end technologies, based on the HPE Apollo 6500 Gen10 Plus, which is purpose-built for AI and analytics workloads, in addition to modeling and simulation workloads that are critical to scientific research. As part of the design, HPE will feature 2nd Gen AMD EPYC processors delivering advanced computational performance, and 384 NVIDIA A100 Tensor Core GPUs for accelerated compute to target AI model development, training, and inferencing.
To support AI training needs that require processing and storing large quantities of data, HPE will also deliver four petabytes of storage using HPEs Cray Clusterstor E1000 parallel storage system, which is built for large-scale systems, to enable expanded storage capacity. Additionally, with the new supercomputers design, MBZUAI will gain sophisticated liquid-cooling capabilities from HPE to efficiently remove heat from high-power devices, including CPUs, GPUs, memory, and switches.
About Hewlett Packard Enterprise
Hewlett Packard Enterprise (NYSE: HPE) is the global edge-to-cloud company that helps organizations accelerate outcomes by unlocking value from all their data, everywhere. Built on decades of reimagining the future and innovating to advance the way people live and work, HPE delivers unique, open and intelligent technology solutions as a service. With offerings spanning Cloud Services, Compute, High Performance Computing & AI, Intelligent Edge, Software, and Storage, HPE provides a consistent experience across all clouds and edges, helping customers develop new business models, engage in new ways, and increase operational performance. For more information, visit: http://www.hpe.com.
About Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)
MBZUAI is a graduate, research university focused on artificial intelligence, computer science, and digital technologies across industrial sectors. The university aims to empower students, businesses, and governments to advance artificial intelligence as a global force for positive progress. MBZUAI offers various graduate programs designed to pursue advanced, specialized knowledge and skills in artificial intelligence, including computer vision, machine learning, and natural language processing. For more information, please visit http://www.mbzuai.ac.ae.
AMD, the AMD Arrow logo, EPYC, and combinations thereof, are trademarks of Advanced Micro Devices, Inc. Other names are for informational purposes only and may be trademarks of their respective owners.
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Mohamed bin Zayed University of Artificial Intelligence Advances the UAE's National Strategy for AI with New Supercomputer Built by Hewlett Packard...
REPORT | Music And Artificial Intelligence: A Bond Thats Growing By Leaps And Bounds – Ludwig Van
Image by Gerd Altmann (CC0C/Pixabay)
Over the last decade or so, artificial intelligence (AI) has become more and more prevalent in everyday life, from the online ads that seem to know just what youre looking for to music composition and other creative applications.
The very notion of making music with AI raises questions about the nature of creativity, and of the future for human composers. From useful tools to pioneering prototypes, heres a look at some of the most recent innovations that use AI in the music writing process.
DoReMIR Music Research AB recently announced the launch of ScoreCloud Songwriter, a tool that turns original music into lead sheets. The software uses the information recorded with a single microphone, and can include vocals and instruments. Various AI protocols separate out the vocals, and then transcribes the music, including melody and chords, along with the lyrics in English. What youll get is a lead sheet with the melody, lyrics, and chord symbols.
Many established and emerging songwriters are brilliant musicians but struggle with notating their music to make it possible for others to play, explained Sven Ahlback, DoReMIR CEO, in a media release. Our vision is that ScoreCloud Songwriter will help songwriters, composers, and other music professionals, such as educators and performers. It may even inspire playful use by lovers of music who never thought they could write a song. Our hope is that it will become an indispensable tool for creating, sharing, and preserving musical works.
Harmonai is a company that creates open-source models for the music industry, and Dance Diffusion is their latest innovation in AI audio generation. It uses a combination of publicly available models to create audio bits so far, about 1-3 seconds long from nothing, as it were, which can then be interpolated into longer recordings. Since its AI, the more users enter audio files for it to learn from, the more it will evolve and develop. If youre interested in how Dance Diffusion came together, theres a video interview with the creators here.
Heres one of their projects, an infinite AI bass solo that has been playing since January 27, 2021. Its based on the work of the late musician Adam Neely.
Its still in the testing stages, but its implications are profound.
Googles new AudioLM bases its approach to audio generation on the way language is processed. It can generate music for piano with a short excerpt of input. Speech combines sounds into words and sentences, in the same way the music is about individual notes that come together to form melody and harmony. Google engineers used the concepts in advanced language modelling as their guide. The AI captures melody as well as overall structure, and the details of the audio waveform to create realistic sounds. It reconstructs sounds in layers designed to capture the nuances.
Metas new AudioGen uses a text-to-audio AI model to create sounds as well as music. The user enters a text prompt, such as wind blowing, or even a combination, such as wind blowing and leaves rustling and the AI responds with a corresponding sound. The system was developed by Met and the Hebrew University of Jerusalem, and it is able to generate sound from scratch. The AI can separate different sounds from a complex situation, such as several people speaking at once. Researchers trained the AI using a mix of audio samples, and it can generate new audio beyond its training dataset. Along with sounds, it can generate music, but that part of its functionality is still in its infancy.
With AI music generation in its infancy, its easy to dismiss its future impact on the industry. But, it cant be ignored.
An electronic band by the name of YACHT recorded a full album with AI in 2019, using technology thats already been surpassed. Essentially, they taught AI how to be YACHT, and it wrote the music. The band then turned it into their next album.
Im not interested in being a reactionary, YACHT member and tech writer Claire L. Evans mentioned that ambivalence in a documentary about their 2019 AI-assisted album Chain Tripping (as quoted in Tech Crunch). I dont want to return to my roots and play acoustic guitar because Im so freaked out about the coming robot apocalypse, but I also dont want to jump into the trenches and welcome our new robot overlords either.
The onslaught of new technology is relentless. The only choice is to hop on the train.
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Anya Wassenberg is a Senior Writer and Digital Content Editor at Ludwig Van. She is an experienced freelance writer, blogger and writing instructor with OntarioLearn.
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REPORT | Music And Artificial Intelligence: A Bond Thats Growing By Leaps And Bounds - Ludwig Van
CloudFabrix Was Named a Leader and Innovator in the 2022 Gigaom Radar for Artificial Intelligence for Operations (AIOPs) – Yahoo Finance
MSPs, Edge Providers, and Large Enterprises will find CloudFabrix's domain-agnostic, distributed, Robotic Data Automation fabric-based AIOps model appealing
PLEASANTON, Calif., Oct. 13, 2022 /PRNewswire/ -- CloudFabrix the inventor of Robotic Data Automation Fabric Platform and the Data-centric AIOps Leader, was named a Leader and Innovator in the 2022 Gigaom Radar for AIOps report for a 2nd consecutive year. The report evaluated 24 major AIOps vendors across Key criteria and evaluation metrics that should be applied when selecting an AIOps solution. The report segregates the 24 vendors across Leaders, Challengers, and New Entrants. CloudFabrix was identified as a Leader, Fast Mover, and Innovator that provides a complete AIOps solution, with a unique Robotic Data Automation Fabric and Distributed AIOps model, including for AIOps at the edge.
According to the report, "This year proved to be one of explosive growth in AIOps tooling and solutions. In some cases, AIOps functionality was achieved by bolting an artificial intelligence and machine learning (AI/ML) engine to existing software, via acquisition or internal development, and marketing it as an AIOps solution. Other vendors built entire platforms around homegrown or acquired AI/ML, jumping into a crowded arena competing with pure AI/ML solutions and platform tools." CloudFabrix's platform is homegrown, built with microservices, is cloud native and can run entirely in the cloud, in a hybrid deployment, or on-premises.
This year's report points out one key differentiation, among the 24 surveyed vendors dividing them into domain-agnostic and platform solutions and what it means for end users. The domain-agnostic solutions can be added to any environment with minimal interruption to the business, while platforms may require the displacement of several existing monitoring solutions.
CloudFabrix scored high ranks across the 3 categories, as identified by the report -
CloudFabrix is among 6 of the 24 vendors identified as Leaders and Fast Movers CloudFabrix's Data-centric AIOps solution is in the domain-agnostic category and integrates well with existing solutions, a business may have.
Story continues
CloudFabrix is among 4 of the 24 vendors identified as Innovation players Each provides a complete AIOps solution with unique capabilities. CloudFabrix, with its Robotic Data Automation Fabric, provides a distributed AIOps model that's unique.
CloudFabrix is among 3 of the 24 vendors identified as AIOps for Edge vendors In the area of emerging technologies, IoT and other edge technologies may require some consideration. A few vendors have explored AIOps for the edge and made strides.
The report identifies CloudFabrix's key capabilities -
Ease of Deployment - CloudFabrix unifies observability, AIOps, and automation within a single SaaS cloud platform (cfxCloud) built on AWS. The platform is also available in AWS Marketplace.
Composable Services - RDAF powers multiple services deployed on top of the AIOps platform, including Log Intelligence, Asset Intelligence, and Service Intelligence.
Continuous ML - Unsupervised and supervised learning are both provided, along with topology detection with data models. Supervised learning is used in the Incident Room to detect possible root causes.
Broad data integration support RDAF is used to integrate data with new sources. In terms of IT operations management (ITOM) and SIEM, log data can be ingested from Splunk and Elasticsearch, and many more.
Log Intelligence - New this year is its Log Intelligence service.
Data Fabric for Edge AI /IoT -The low-latency distributed data fabric allows cfxCloud to ingest, integrate, transform, and load data from or to any system.
Low Code / No Code - users can interact with and operationalize it using a set of more than 800 existing bots and create others via a self-service pipeline.
Service Management - Support is also provided for datastores and data lakes, IT service management (ITSM), configuration management database (CMDB), the collaboration platforms Slack, Microsoft Teams, and Twilio; and Terraform, Ansible, and Chef for automation.
Supporting Quotes
"CloudFabrix continues to impress us with its innovation and its ability. They have shown a pulse on the AIOps market and a quest to constantly improvise in the areas where they were at a disadvantage, across the 2 years we have evaluated them. We are hopeful they continue on this path as Digital Transformation and AIOps are becoming mainstream for enterprises," said Ron Williams, Principal Analyst, Gigaom.
Shailesh Manjrekar, Vice President of AI and Marketing, CloudFabrix said, "We are delighted and honored to be recognized as a leader by Gigaom for 2 consecutive years. This endorses us as a "Fast Mover," demonstrated by our recent launch of "Persona-based Composable Analytics for AIOps." He further asserted, "Our success and scalability are demonstrated by our recent wins with large global MSPs and Enterprises. We continue to strive to delight our customers and make their autonomous enterprise journey, a reality by democratizing Data-First, AI-First, and Automation everywhere strategies."
Resources:
About CloudFabrix
CloudFabrix is the leading Data-centric AIOps Platform vendor and the inventor of Robotic Data Automation Fabric (RDAF). RDAF delivers integrated, enriched and actionable data pipelines to operational and analytical systems. RDAF unifies Observability, AIOps and Automation for Operational Systems and enriches analytical systems. CloudFabrix empowers Business and IT leaders with AI-powered actionable intelligence to make faster and better decisions and accelerate IT planning and Autonomous operations. For more information, visit cloudfabrix.com
Media Contact / Press Enquiry:Shailesh Manjrekar346592@email4pr.com408-421-4214
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CloudFabrix Was Named a Leader and Innovator in the 2022 Gigaom Radar for Artificial Intelligence for Operations (AIOPs) - Yahoo Finance
Genomic Testing Cooperative and its Co-Op Members First to Use Artificial Intelligence to Distinguish Between 45 Hematologic and Solid Neoplasms Using…
IRVINE, Calif.--(BUSINESS WIRE)--Genomic Testing Cooperative, LCA (GTC) announced that its innovative artificial intelligence (AI) algorithms are now formally implemented in daily use to aid pathologists in the diagnosis and interpretation of molecular findings of genomic profiling.
GTCs RNAnalysis algorithm is used to distinguish between 45 different diagnostic classes providing probability scores. This algorithm is complemented by a second algorithm called TraceWork. When needed, TraceWork is used to distinguish between two diagnostic entities determined by RNAnalysis to be of similar high probability score.
Results of validation of these algorithms are now published in The American Journal of Pathology, a part of Elsevier's Journal Network (DOI:https://doi.org/10.1016/j.ajpath.2022.09.006). For example, independent blind testing of RNAnalysis algorithm showed correct first-choice diagnosis in 100% of acute lymphoblastic leukemia, 88% of acute myeloid leukemia, 85% of diffuse large B-cell lymphoma, 82% of colorectal cancer, 49% of lung cancer, 88% of chronic lymphocytic leukemia and 72% of follicular lymphoma. The TraceWork algorithm distinguished between lung cancer and colorectal cancer with 97.2% sensitivity and 94.5% specificity, between Hodgkin lymphoma and normal lymph node with 95.4% sensitivity and 100% specificity, between follicular lymphoma and diffuse large B-cell lymphoma with 95.9% sensitivity and 93.1% specificity, and between breast cancer and ovarian cancer with 100% sensitivity and 94.2% specificity.
The information provided by these algorithms are used in the context of clinical and other molecular and pathologic findings and not meant to replace the need for physicians clinical decision, said Dr. Maher Albitar, founder, chief medical officer, and chief executive officer of GTC. We believe that transcriptomic data when combined with AI provides an efficient and effective information that can replace the need for large number immunohistochemical staining and flow cytometry testing, especially when tissue samples are scant, Dr. Albitar added.
Dr. Andre Goy, Chairman & Chief Physician Officer at John Theurer Cancer Center and Academic Chairman of Oncology at Hackensack Meridian School of Medicine, stated, Precision diagnosis is extremely important for the practice of precision medicine. Todays RNA and DNA profiling generates big data that requires sophisticated algorithms to decipher the clinical relevance of this data. GTCs molecular profiling and algorithms had helped us resolve numerous diagnostically challenging cases and the results made a difference in patients management and outcome.
Dr. Aamir Ehsan, CEO/ President, Medical Director and board-certified hematopathologist and molecular geneticist of CorePath laboratories, at San Antonio, Texas, who is a collaborator and coauthor on the published work, said, Unlike AI and imaging, transcriptomic data and AI incorporates immunohistochemistry and flow cytometry data as well as numerous additional biomarkers, but more importantly allows us to look at each biomarker individually to make the final pathologic decision. This represents major advances in the practice of pathology.
It is estimated that approximately 10% of all cancer cases are misdiagnosed and 4% of solid tumors are presented as cancer of unknown primary CUP.
About Genomic Testing Cooperative, LCA
Genomic Testing Cooperative (GTC) is a privately-owned molecular testing company located in Irvine, CA. The company operates based on a cooperative (co-op) business model. Members of the co-op hold type A shares with voting rights. The company offers its patron members a full suite of comprehensive genomic profiling based mainly on next generation sequencing. Molecular alterations are identified based on rigorous testing with the aid of specially developed algorithms to increase accuracy and efficiency. The clinical relevance of the detected alterations is pulled from numerous databases using internally developed software. Relevance of findings to diagnosis, prognosis, selecting therapy, and predicting outcome are reported to members. The co-op model allows GTC to make the testing and information platform available to members at a lower cost because of a lower overhead. For more information, please visit https://genomictestingcooperative.com/.
Forward Looking Statements
All of the statements, expectations and assumptions contained in this press release are forward-looking statements. Such forward-looking statements are based on the GTC managements current expectations and includes statements regarding the value of comprehensive genomic profiling, RNA profiling, DNA profiling, algorithms, therapy, the ability of testing to provide clinically useful information. All information in this press release is as of the date of the release, and GTC undertakes no duty to update this information unless required by law.
Piggly Wiggly Midwest Partners with Focal Systems to Leverage Artificial Intelligence and Automation to Transform the Shopper Experience – Grocery…
About Focal Systems:
Founded in 2015 in San Francisco out of Stanfords Computer Vision Lab, Focal Systems is the industry leader in retail automation. Our mission is to automate and optimize brick and mortar retail with state-of-the-art deep learning and AI. We have pioneered the worlds first Self-Driving Store- an OS that revolutionizes how stores are run. Focal has raised more than $40M to date and scaled solutions on three continents in hundreds of stores, with over 100,000 cameras deployed. Learn more at: https://focal.systems.
Contact:
Lizzy Harris for Focal Systems
[emailprotected]
1-303-503-1136
About Piggly Wiggly:
Building on its more than 100-year history in the grocery business, Piggly Wiggly continues to grow its presence with stores throughout the Midwest, South and Northeast. C&S Wholesale Grocers, Inc. operates corporate stores and services independent franchisees under a chain-style model. This unique grocery store offers the selection and assortment of a national chain, with the service and local customization of a community-based retailer. Each store contains specialized local assortments to meet local shoppers needs.
Piggly Wiggly Midwest: https://www.shopthepig.com/
Piggly Wiggly Carolinas: https://www.thepig.net/
About C&S Wholesale Grocers, Inc. C&S Wholesale Grocers, Inc. is an industry leader in supply chain solutions and wholesale grocery supply in the United States. Founded in 1918 as a supplier to independent grocery stores, C&S now services customers of all sizes, supplying more than 7,500 independent supermarkets, chain stores, military bases and institutions with over 100,000 different products. We are an engaged corporate citizen, supporting causes that positively impact our communities. To learn more, please visit http://www.cswg.com.
C&S Media Contact:
Lauren La Bruno
Vice President of Communications, Change Management and Community Relations
C&S Wholesale Grocers, Inc.
[emailprotected]
C&S Investor Relations:
Julie Drake
Vice President, Assistant Treasurer
C&S Wholesale Grocers, Inc.
[emailprotected]
Piggly Wiggly Marketing Contact:
Molly Rippinger
Director, Marketing
Piggly Wiggly Midwest
[emailprotected]
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Piggly Wiggly Midwest Partners with Focal Systems to Leverage Artificial Intelligence and Automation to Transform the Shopper Experience - Grocery...
Can artificial intelligence help identify best treatments for cancers? LSU researchers say yes – The Advocate
A team of LSU researchers has developed a way to determine which drug therapies work best against an individual's unique type of cancer, possibly providing a way to find cures more quickly and make treatment more affordable.
The interdisciplinary team includes researchers from the School of Veterinary Medicine, College of Science, College of Engineering and the Center for Computation & Technology. It created CancerOmicsNet, a new drug discovery engine run by artificial intelligence.
Using algorithms originally designed to map complex social networks, like those utilized by Facebook, researchers generated three-dimensional graphs of molecular datasets that include cancer cell lines, drug compounds and interactions among proteins inside the human body.
The graphs are then analyzed and interconnected by AI, forming a much clearer picture of how a specific cancer would respond to a specific drug.
Dr. Michal Brylinski, associate professor of computational biology at LSU, said that the team used established datasets to train the CancerOmicsNet engine into using artificial intelligence.
"Once its trained, then you can ask for something that you dont know and this is the input data," he said. "So you ask what inhibitor you think is going to be effective against this cancer and then AI makes a prediction. Thats the implication to unseen data and then something like that goes to a wet lab and we can validate it.
Wet lab research was conducted by researchers at the LSU School of Veterinary Medicine and led by associate professor of research Brent Stanfield.
They developed the AI algorithm and everything, so our role in the study is just to be the practical applications of the technology," Stanfield said. "They developed the algorithm, identified the drugs and then we tested the drugs in our high-capacity systems to demonstrate their efficacy to kill cancer cells.
Researchers studied notoriously aggressive breast, prostate and pancreatic cell lines to train the AI to recognize connections between specific cancers and cancer drugs that control the production of the enzyme kinase within the body.
Kinase acts as a biological catalyst for cell communication and cell growth. Using drugs that lower kinase activity can suppress the growth of cancerous cells.
Brylinski said the research team used CancerOmicsNet to pick out six combinations of cancer cell lines with the drugs likely to be the most toxic to their gene expression profile and tested them, with encouraging results.
According to acceptable criteria, four out of six worked and this success rate is extremely high because if you just picked up six random drugs and say those drugs are going to work on this cancer, then theyre probably not going to work on that cancer," he said. "Four out of six was very encouraging and this is where we stand right now."
Using CancerOmicsNet like molecular speed dating, the AI can help researchers quickly match cancer cell lines with the drugs likely to be the most toxic to their growth and genetic profile.
Brylinski said knowledge gained through CancerOmicsNet can help overcome the challenge of determining how effective a particular kinase-inhibiting drug could be in the future.
The ultimate goal, he said, is to expand their research to potentially apply it in clinical settings.
"If we have a patient with a certain cancer, they can do a biopsy and then they can profile this cancer with respect to gene expression, genetic mutations and everything," Brylinski said. "Then they can input that data to CancerOmicsNet and it can suggest some therapy for this particular cancer and say this drug could be effective and 'another drug could not be effective.'
The effectiveness of various cancer drugs was initially believed to be tied to molecular consistency, the idea that cancer treatment should be targeted to a specific to a location in the body.
Michelle Collins, dean of the College of Nursing and Health at Loyola University New Orleans and a scientist not involved in the LSU research, said CancerOmicsNet is an example of how our current medical understanding of cancer treatment meets advances in genetic studies and AI.
When cancer drugs first came out, they were one size fits all and werent really tailored to the individual and so you see the medications work better on some people than others," she said. "And with the advent of genetics and genomics, which are the future of medicine, were now going to be able to tailor treatments to the patient and not just in oncology.
Collins said she sees CancerOmicsNet being extremely beneficial to oncological studies and treatment in the future.
I think it has the potential to really revolutionize the field of oncology, because well be able to treat people with medication that is more timely tailored to them," she said. "All of that is good if youre a patient with cancer.
Brylinksi said that the ability to treat cancer with a more direct, focused clinical approach makes him excited to see how CancerOmicsNet develops over time.
"I dont know if were going to make some major breakthrough in oncology any time soon, but were contributing pieces where if enough people are doing this, the whole field is moving forward towards the goal of improving human health," he said. "Were very happy that we can make some contribution, which might not be a huge breakthrough down the road, but definitely something that is useful to improving human health and thats really cool actually.
Investing in artificial intelligence: The pros and cons – iNews
Artificial intelligence: its one of those mind-bending subjects that provokes fascination yet is misunderstood by almost everyone (myself included). If you bring it up in the pub to sound brainy, the conversation might only go as far as Alan Turing, Deep Blue versus Garry Kasparov and perhaps the new series of BBC drama The Capture, in which foreign spies seem to use AI to manipulate CCTV and live broadcasts.
But AI has long moved beyond the realms of gripping fiction and headline-grabbing experiments into the real world. For instance, DeepMind, a British subsidiary of Alphabet, recently released almost the entire make-up of the protein universe, mapped for the first time by its AI programme AlphaFold. This data is already being used to advance our understanding of life-threatening illnesses and help protect honeybees.
Amid all the scaremongering about AI, perhaps we should be more aware of these positive developments, particularly if were investors. Funding technology that is tangibly solving the worlds trickiest problems surely thats responsible investing at its finest?
Besides, AI applications that drive efficiency, reduce costs, serve vital needs, and cement a companys competitive advantage should generate significant value. Thats not to be sniffed at in this current investing climate.
The Sanlam Artificial Intelligence Fund has specifically hit on AI as a way to back winners in the stock market. Its managers Chris Ford and Tim Day marked the funds fifth anniversary recently by sharing some intriguing insights on how AI has improved in recent times.
Things that people called pipe dreams when we launched the fund in 2017 are now happening, says Chris Ford. What was impossible is now possible.
Examples include Alibabas equivalent scoring better than humans in Stamford Universitys reading and comprehension test, and the Canadian platform Blue Dot spotting the spread of Covid-19 nine days before the World Health Organisation put the alert out.
How has this translated into hard financial returns? The 715.5m fund has had an annualised return of 18.2 per cent since it was established, which is respectable, and its top performers have included household names like Tesla, Netflix, Microsoft and Ocado, alongside lesser-known AI innovators like NVIDIA, Zendesk, and Appen.
The managers even have their own AI application (Orbit) to help them stay across things. Its ongoing charges figure is 0.8 per cent not dirt cheap, but not bad for an active fund.
Do actively managed thematic funds like this have the edge, not just over their cheaper rivals but within the broader investment universe?
Sanlams fund, a traditional open-ended unit trust, has comfortably beaten the MSCI World index, which has had an annualised return of 8.41 per cent over the past five years. By contrast, only 39 per cent of thematic exchange-traded funds (ETFs) have survived and outperformed the index over that same period, according to data from Morningstar.
But the funds performance has markedly dipped in recent times, as the global rout in stock markets hits technology shares particularly hard. This is the downside of thematic investing: clever use of AI may not be the main reason why a company flourishes, or why investors feel well-disposed towards it.
The likes of Tesla, Ocado and Netflix can end up in choppy waters when investing conditions change, and it becomes clear that these firms have been overvalued by the market for what they do. Thematic investing can also lead to a good deal of overlap in your portfolio, with the same names cropping up again and again. This can undermine diversification and add to your risks.
Also, whilst many of the Sanlam holdings are doing great work (like Alphabets DeepMind), there is a good reason why its not classed as socially responsible. EthicsGrade is a ratings agency specialising in understanding the risks stemming from digitalisation, particularly AI, and it has awarded a top A rating to only a handful of firms, including Microsoft and Deutsche Telekom.
Fewer than a third of the 302 major companies it graded have a score of C or above. Too many were unrated altogether because they either ignored or provided little to no details on governance and ethics policies relating to AI.
Experts mostly agree that the more sinister AI possibilities as depicted in The Capture still look far-fetched. But its worrying that many of the major companies we buy from and invest in are being cavalier regarding privacy breaches, data misuse, racial and gender discrimination, the creation of harmful weapons and other potential dangers of AI.
AI is not going anywhere (particularly since the Chinese government is investing heavily in AI research and development). If it proves as beneficial for its first movers as many believe, AI could become the first big success story of so-called thematic investing, previously dismissed as no more than a trendy gimmick that promises more than it can deliver.
The big question is whether this technology will be treated with enough care by its creators and investors. If not, disappointing returns will be the least of our problems.
Originally posted here:
Investing in artificial intelligence: The pros and cons - iNews
WISeKey and OISTE.org Foundation Presented AI and Digital Identity at the Global Dialog on the Interplay Between Human Intelligence and Artificial…
WISeKey and OISTE.org Foundation Presented AI and Digital Identity at the Global Dialog on the Interplay BetweenHuman IntelligenceandArtificial Intelligence
Geneva October 10, 2022 - WISeKey International Holding Ltd (WISeKey ) (SIX: WIHN, NASDAQ: WKEY), a leading global cybersecurity, AI, Blockchain and IoT company and the OISTE.org foundation presented the subject of AI and Digital Identity at the Global Dialog on the interplay betweenHuman IntelligenceandArtificial Intelligence.
TheUnited Nations Alliance of Civilizations (UNAOC) and theFundacin Onuartare co-organizing a high-level global dialogue on the interplay betweenHuman IntelligenceandA!for better public affairs management, to pave the way for new private sector initiatives that bolster positive global development driven by innovation and inclusiveness.
AI, in the service of humanity, can drive diversity, respect and progress for all through innovation. Moving forward under a strong public-private partnership is essential to this end. The Global Dialogue aims to further strengthen this cooperation.
The two-day event will be inaugurated by high-level keynote speakers, with participants from the public and private sector bringing forth their expertise in the field. Speakers will discuss and share with the audience how their organizations and companies approach AI and AI-enabled technologies and expound on their vision moving forward.
Carlos Moreira, WISeKeys Founder and CEO, during his presentation highlighted the need to use decentralized technologies related to Digital Identity and Blockchain which are in line with the United Nations Sustainable Development Goals aiming on providing every person on the planet with a solid and tamper-proof digital identity based on common, interoperable standards by 2030.
A digital identity under the control of the person is a fundamental human right which is not currently protected neither understood. It is also an endangered right due the exponentiality of the technology. Current digital technologies track and scrutinize us by taking into consideration onlyour consumer identity and not our human identity.
The digital economy considers every click, search or like as an asset to be monetized. Our lives, reflected in cyberspace, are plundered for behavioral data for the sake of a system that converts our freedom into profit. We are quietly being domesticated into accepting as normal that decision rights vanish before we even know that there is a decision to make.
We, collectively as humans, have to decide if we are building a better future for humanity with the help of magnificent technologyor building a future of better technology at the expense of humanity.Weve been down this road before, and it didnt turn out well. We collectively made the wrong decisionor, better said, we didnt make the right decision fast enough. We didnt put humanity first and instead got caught up in the promise of technology.A new awareness infused by a human-rights based approach that consider each individual netizen as a dignified moral being, worth of respect, is required. Otherwise, our connectivity will continue to offer a perverse amalgam of empowerment inextricably layered with diminishment, said Mr. Moreira.
About WISeKeyWISeKey (NASDAQ: WKEY; SIX Swiss Exchange: WIHN) is a leading global cybersecurity company currently deploying large-scale digital identity ecosystems for people and objects using Blockchain, AI, and IoT respecting the Human as the Fulcrum of the Internet. WISeKey microprocessors secure the pervasive computing shaping todays Internet of Everything. WISeKey IoT has an installed base of over 1.6 billion microchips in virtually all IoT sectors (connected cars, smart cities, drones, agricultural sensors, anti-counterfeiting, smart lighting, servers, computers, mobile phones, crypto tokens, etc.). WISeKey is uniquely positioned to be at the leading edge of IoT as our semiconductors produce a huge amount of Big Data that, when analyzed with Artificial Intelligence (AI), can help industrial applications predict the failure of their equipment before it happens.
Our technology is Trusted by the OISTE/WISeKeys Swiss-based cryptographic Root of Trust (RoT) provides secure authentication and identification, in both physical and virtual environments, for the Internet of Things, Blockchain, and Artificial Intelligence. The WISeKey RoT serves as a common trust anchor to ensure the integrity of online transactions among objects and between objects and people. For more information, visitwww.wisekey.com.
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Disclaimer:This communication expressly or implicitly contains certain forward-looking statements concerning WISeKey International Holding Ltd and its business. Such statements involve certain known and unknown risks, uncertainties and other factors, which could cause the actual results, financial condition, performance or achievements of WISeKey International Holding Ltd to be materially different from any future results, performance or achievements expressed or implied by such forward-looking statements. WISeKey International Holding Ltd is providing this communication as of this date and does not undertake to update any forward-looking statements contained herein as a result of new information, future events or otherwise.This press release does not constitute an offer to sell, or a solicitation of an offer to buy, any securities, and it does not constitute an offering prospectus within the meaning of article 652a or article 1156 of the Swiss Code of Obligations or a listing prospectus within the meaning of the listing rules of the SIX Swiss Exchange. Investors must rely on their own evaluation of WISeKey and its securities, including the merits and risks involved. Nothing contained herein is or shall be relied on as, a promise or representation as to the future performance of WISeKey.
China’s Artificial Intelligence Market Will Exceed US$26.7 Billion by 2026, according to IDC EMSNow – EMSNow
IDC recently released the IDCWorldwide Artificial Intelligence Spending Guide. Data shows that total global IT investment in artificial intelligence (AI) in 2021 was US$92.95 billion, expected to increase to US$301.43 billion in 2026, and the compound annual growth rate (CAGR) was about 26.5%. As for the China market, IDC predicts that Chinas AI investment is expected to reach US$26.69 billion in 2026, accounting for about 8.9% of global investment, ranking second in the world among other countries. In recent years, more and more enterprises have become involved in the Digintelligence Era and started the deployment of digital transformation (DX) and intelligent upgrading, which has thus spawned more demand for AI. Driven by policies, technologies, and markets, AI empowering industries is becoming a mainstream development trend.
Technology Dimension
Over the next five years, the hardware market will be the largest primary market in Chinas AI market, accounting for more than half of the total AI investment. IDC predicts that Chinas IT investment in the AI hardware market will exceed US$15 billion in 2026, close to that of the AI hardware market size of the United States. With the gradual improvement of AI infrastructure construction, hardware growth will gradually slow down, with the five-year CAGR remaining around 16.5%. The server market, as the main part of the hardware market, will account for over 80% over the five-year forecast period.
At the same time, the services market will expand at a faster pace, with the five-year CAGR expected to be about 29.6%. Total investment in the services market is expected to exceed US$4 billion in 2026, nearly four times the investment in 2021, with significant market growth. The AI services market as defined by IDC is mainly dominated by the IT services segment. IDC predicts that IT services will lead the services market growth at a five-year CAGR of 31.0%.
From the perspective of AI software, under the joint promotion of the gradual development of technologies including machine learning (ML) and computer vision, Chinas policy environment, and the gradually diversified customer needs, Chinas AI software market share will increase year by year, and more than 25% of the AI marketrelated IT investment will flow to software in 2026. In terms of growth rate, the AI software market will become the fastest-growing primary market during the five-year forecast period, with a five-year CAGR of about 30.4%. From the perspective of the technology segment, AI platforms will absorb more than 70% of software-related spending over the next five years and will become an important driving force for software market growth at a five-year CAGR of 33.1%.
Industry Application
IDC predicts that the AI-related spending of users in the four major endpoint industries professional services, government, finance, and telecom will continue to lead over the five-year forecast period, which will collectively exceed 60% of the total spending of Chinas AI market. Specifically, local governments. AI spending will lead AI investment growth with a five-year CAGR of 24.3% and is expected to exceed US$2.51 billion in 2026; and it is expected that the central government will have a five-year CAGR of 19.4% and reach US$1.37 billion in 2026. The market size of the financial sector represented by banks will continue to grow over the next few years, with the five-year CAGR expected to exceed 21.0%. In addition, the construction, discrete manufacturing, and healthcare industries have also achieved high growth rates, jointly promoting the development and application of Chinas AI. In the future, AI will be applied in various industries, with expansion in both width and depth. It will further effectively support the industries to achieve intelligent marketing and decision-making. At the same time, the deep integration of AI with industries will stimulate more potential and foster more business opportunities.
Use Case
Based on research conducted on the industries mentioned earlier, IDC Worldwide Artificial Intelligence Spending Guide covers 29 typical key AI use cases, which will be updated to reflect the market dynamics. Three use cases, namely, augmented customer service agents, public safety and emergency response, and smart business innovation and automation, will continue to remain dominant. The three together will account for more than 30% during the five-year forecast period. Currently, there are mature applications of AI in various industry use cases. It completes independent judgment and behavior learning through technologies, such as deep learning, computer vision, and image recognition, to solve a variety of complex tasks, laying an important foundation for the intelligent transformation of the industry. In use cases, customer service agents are developing rapidly, with cases in finance, retail, and other industries. Public safety and emergency response are mainly involved in the field of government security, and biometrics is used for fingerprint and face recognition. In the future, with the increasing development of AI chips, 5G, and other technologies, AI will also be better implemented in more fields.