Every organization now relies on technology to remain competitive. Downtime is more expensive than ever and the volume and variety of machine data generated as logs, metrics, and traces means the old way of managing availability and performance is no longer an option.
InsightFinder, founded by Dr. Helen Gu, a system machine learning expert, helps companies like Dell, Credit Suisse, and China Mobile to detect system anomalies without thresholds, predicting severe incidents hours before they happen, and automatically pinpointing root causes. Customers report four to six hours of downtime reduction per incident and tens of thousands of dollars in cost savings monthly.
To support increased market demand, the company today announced a two million dollar investment from leading venture capital group Fellows.Fund, alongside the founder of a $100B+ software company, Silicon Valley Future Capital, Eastlink Capital, Brightway Future Capital and more than a dozen executives at Facebook, Uber, Pinterest, Amazon, and Airbnb. According to Alex Ren, Fellows.Fund Managing Director, “InsightFinder’s groundbreaking approach was vetted by the experts in the field, and the Fellows’ network and connections are poised to foster the company’s success.”
The company also announced it recently closed a deal with NTT DATA, the Japanese multinational information technology service company headquartered in Tokyo. NTT DATA will use technology from InsightFinder to help its customers reduce downtime for critical systems. Additionally, InsightFinder extended its existing partnership with Apprendis, makers of the Inq-ITS e-learning platform.
InsightFinder is also expanding its leadership team to include new Chief Revenue Officer, John Whittington. John has over 25 years of enterprise software sales experience. He co-founded BlueStripe Software and grew the business to a successful exit to Microsoft. According to John, “I’ve helped introduce monitoring technology to enterprise customers for nearly three decades and have never seen a stronger product than InsightFinder or a market more poised for disruption.”
Edge AI Applications Broaden Horizons for Innovations and Opportunities Across Industries
The high data-driven nature of IoT (Internet of Things) systems calls for the need for technologies such as edge AI (Edge computing and Artificial Intelligence). Today, businesses realize the fact that edge AI is crucial not only because it is revolutionizing industries but also because it is our ultimate future. The technology gains much attention at present as it enables processing of data at the edge, i.e. directly on the device or on the server near the device instead of the cloud, thereby reducing latency in making critical decisions, increasing the speed of processing tasks and mitigating any delayed communication with the cloud. In addition, it reduces bandwidth requirement and cost by processing it on site. Edge AI also offers high data security as it operates in a closed network, making it difficult to steal information. These, along with many others, are important reasons for businesses to incorporate edge in their applications.
Edge AI finds applications in many areas. Current examples include Amazon’s Alexa or Apple’s Siri, smartphones with face recognition, mapping and cartography in drones, autonomous vehicles, smart speakers, drones and robots. Implementation of edge AI is also seen in various industries such as healthcare, manufacturing, transportation, retail, and more for upgrading their operations to ensure higher productivity, accuracy, efficiency, and safety. Here’s a look:
Edge AI in Healthcare –
Use of edge computing and AI in medicine helps promote patient care and operational efficiency. It also facilitates enhanced data security which is important for smart hospitals to carry out their tasks efficiently. Healthcare firms are able to perform medical tasks such as remote monitoring of patients, diagnostics, precise thermal screening, inventory management, and prediction of ailments.
Edge AI in Manufacturing –
The manufacturing industry implements edge AI to enhance and protect its processes and resources. It also seeks solutions that enhance productivity, quality, and reduce risks. For example, advanced machine vision or video analytics, an example of industrial edge AI, allows to gauge product quality with great precision. It is capable of detecting even the smallest quality deviations that almost go unnoticed with the human eye and predict machine failure to prevent bottlenecks. Thus, it helps avoid downtime and addresses problems that may lead to machine repairs and requirements.
Edge AI in Transportation –
With an aim to create smart cities where roads, vehicles and buildings communicate with one another, many technology companies adopt edge AI to provide smart cameras that assess traffic in real-time to identify obstructions in the road, reckless drivers and other situations.
Edge AI in Retail –
For long, many retail chains have been implementing customer analytics, which is based on an analysis of completed purchases, i.e. receipt data. Even if this technique helps in getting accurate results, the receipt data does not give information about how people move around the store, what they stop to watch, and the like. With the help of video analytics, retail companies can analyze anonymized data extracted from a video image and get informed about people’s purchasing behavior that can improve customer service and the overall shopping experience.
AI application at the edge is seeing a tremendous growth and companies that are investing and embracing this technology are also growing subsequently. This infers that the market for edge AI is growing by leaps and bounds and has a promising future. A report by Allied Market Research predicts that the edge AI processor market is projected to amass $9.6 billion by 2030, registering a CAGR of 16% during the forecast period 2022-2030. The prime factors propelling the market growth are nothing but the benefits offered by Edge AI and the rise in the adoption of electronic items globally.
In a nutshell, AI on the edge is sure to increase opportunities in the future. It is primed to enhance standards across various sectors, be those standards about safety, speed or accessibility.
Author Bio: Sharmistha Bose has always had a keen interest in reading and writing. An engineering graduate, she forayed into the field of writing due to her love for words and the urge to do something different. Allied Market Research has given her the chance to gain knowledge about different subjects as a Specialist Content Writer. She can be reached at email@example.com
How are Artificial Intelligence (AI) Approaches Being Used to Process and Modify Diamonds?
Artificial intelligence has helped evolve various fields, one of them is the diamond industry. The mentioned industry has gone through various phases as technologies and expertise have continued to develop. The recent few years have brought immense changes to diamonds’ excavation, manufacturing, and modification.
Diamonds are considered of high monetary value, which is why they have attracted various techniques regarding their manufacture. The continuing market value of diamonds has boosted the research regarding the use of AI in this field.
These ideas and approaches have helped bring change from the process of extraction to the complete finishing. It has made the job easier for the manufacturers and added refinement for the customers. Here is a brief overview of the impacts of the AI industry on the diamond industry and how AI approaches are being used to modify diamonds.
AI and Changing Diamond Industry
The change in the diamond industry regarding AI began early in the 1990s and 2000s. It was when some Israeli manufacturers employed some modern technological techniques in the diamond industry. They realized that the most important part of the process was planning and deciding the process. The same plan is used to develop each stone into a refined diamond. Since then, it has continued, and the mentioned industry continues to use AI.
If a plan is programmed using AI for this purpose, it will enhance the stone and make it easier for the manufacturers. AI comes to help enhance the process as it is a collection of multiple programs that consider every aspect of the given job. It is perfect for diamonds as their manufacturing process requires hundreds of considerations. Thus, it takes care of all these to get the manufacturer the perfect piece.
AI can also be employed in the preparation of lab-created diamonds as it uses various programs that can generate an ideal diamond. The uses of AI are not just limited to the use in the mining and polishing process. Rather it helps businesses to keep record of their products and arrange it according to their needs. The huge databases that AI uses brings ease in identification, management, and ease for customers.
As diamond is a valuable commodity, it has required special programs that can cover the process from mining to shipping. Also, the available software can also be used to identify if the real diamond has been exchanged for fake during the shipping process. RockHer is an app that utilizes IBM’s technology for the identification of diamonds.
Uses of AI in the Diamond Industry and Diamond Modification
There are various uses of AI in the diamond industry, and it can be used in the modification of diamonds. Some of these are given as follows:
1. Grading and Analysis
AI enhances the process of diamond grading and analysis using its advanced programs. In contrast to AI, it would cost too much time and energy if it is done traditionally. AI tools ensure that real-time data for a diamond is taken and it is analyzed quickly. Though the process for AI grading of diamonds is not new, it is improving constantly.
It simplifies the diamond planning and drilling process as the decisions are data-driven. It employs scanning and imaging technologies while also bringing forth the use of the latest available software for grading. Thus, it reduces the human effort to the minimum possible, and the use of extensive machinery for grading and analysis is reduced.
It fulfills the aim of creating an attractive diamond that requires minimum human effort. It brings more revenue to the business and reduces costs.
The business of a brand depends on an efficient inventory. It can bring the best to the market and serve the customers with the products that the customers demand the most. If AI is used for diamonds, it can improve the standards with the help of AI programs.
The manufacturer can apply specific grading standards that the customers demand the most, and it will improve business.The availability of AI increases accessibility and thus improving the availability of products.
Another use is that of high accuracy in manufacture that is available in the case of AI, which is not always possible in the case of human beings. The manufacturers can follow market suitability according to popular demand and create diamonds with the required attributes.
The AI-based manufacturing process is flexible and can be used for various procedures. It reduces effort while not affecting the inventory, keeping the business afloat.
3. Improving Diamond Pipeline
The whole process of diamond manufacturing is too complex as it involves various steps from mining to analysis and sale. It is through the use of AI programs that the process is streamlined from the start to the end. The use of these programs reduces the cost of the procedures and makes the process easier. The availability of AI tools makes it possible to get reliable results once, instead of requiring multiple checks.
The job of artificial intelligence starts from the mining process. It is through geological tracking devices and other tools that identify the quality of diamonds. In the case of manual exploration or the use of some other tools, there are chances of being misled by wrong information. The use of AI reduces the chances of error, and it helps in the complete process.
Miners get data through drilling rigs and estimate the costs and the benefits a diamond would bring the investors. Then the diamond is processed using other AI tools required for the remaining process.
4. Using AI for accuracy
AI is considered a reliable tool from mining to grading process. It streamlines the process as it bases the procedure of analysis, grading, or any other purpose on a reliable set of data. It brings accuracy to the results which is far better compared to human-checked data.
Another factor that makes it far better is the constant improvement in AI while in comparison, improvement in human accuracy is relatively slower. The developers of programs can improve their algorithms as they can add further data related to diamonds.
Thus, it won’t be too long when AI-based grading and other processes would be the most-reliable ones for businesses.
Some AI Systems and Technologies Used in Diamond Industry
Various AI systems and technologies have been developed by experts, which have found wide use in the diamond industry. Some of the popular names include DiaCam360, Ringo, Sarine e-Grading, etc. These computer programs have developed through trial and error, thus giving the best possible results to the users.
DiaCam360 is an Israel-based developers’ venture who prepared this tool for the analysis of the color and clarity of the diamond. It is based on various databases which contain diamond pictures and other details. Its databases are GIA-affiliated, giving it credibility.
Ringo is an AI-based tool that can help find customers a diamond according to their specific choice. The choice might include color, shape, budget, etc. Sarine e-Grading is a tool that is being used for grading based on 4C’s. It gives object results that can be relied on.
As AI has continued to develop, the mining process has simplified with the reduced costs. There are AI tools that help identify various factors like groundwater, subterranean ventilation, temperature etc. to see if it would be feasible to mine diamonds. Thus, it reduces the risk facto to ensure that the process is safe for miners.
Tracking systems, wireless devices, detection tools, etc. are connected with AI tools to make mining safer and easier. Also, use of AI helps the miners analyze satellite images to see the environmental impact of mining.
Machine learning has helped in predicting dangers in a timely manner. It keeps the mining persons safe by analyzing data and considering if there would be spike in pumps. These also consider the formation of sludge deposits and ore fragmentation.
Thus, the miner is easily able to mine diamonds, reducing the chances of any untoward happening. Robots using AI have found multiple uses in diamond mines. An example is Western Australia where such robots are being used for load, haul, and dump purposes in diamond mines. These are automated machines utilizing AI for their job.
GIA first started testing use of AI for diamond clarity grading in 2020 partnering with IBM. They aim to expand it further to other domains as well.
The development of artificial intelligence (AI) has brought human beings some unparalleled comforts. The diamond industry also benefits from the developments in these fields and has brought programs and tools that help the process from manufacture to refinement and sale. These tools make it easier to determine quality, modify the available diamonds and analyze their specific traits. It reduces too much human interaction and leads to adding precision. The use of AI reduces the chances of error and adds to the quality of the product. Moreso, the addition of new developments to this field will enhance the mentioned technology further in the future.
Resecurity Brings AI-powered Cyber Threat Intelligence to Singapore
California-based cybersecurity company showcases innovative cyber threat intelligence and digital risk management technologies at Milipol Asia-Pacific 2022 (APAC)
Resecurity®, a cybersecurity and intelligence company, showcased its next-generation cybersecurity platform at the 2022 MILIPOL Asia-Pacific (APAC) conference in Singapore. The MILIPOL APAC event welcomed over 7,000 government and law enforcement leaders and 300 exhibitors to share their experiences, best practices and expertise regarding the myriad of security challenges facing local and regional government security forces.
Government organizations face sophisticated and ever-evolving security threats that have led to record cyber incidents in 2021. To help arm government forces with the latest knowledge and technology, MILIPOL APAC focused on connecting homeland security organizations and commercial innovators in emerging markets like cybersecurity to enhance national resilience and public safety.
“Resecurity is proud to have participated in this year’s MILIPOL APAC event. As governments protect and respond against increasing cyber threats, we must provide nations with the insights and technology they need to keep pace with adversaries,” said Gene Yoo, CEO of Resecurity. “Resecurity aims to streamline cyber risk and intelligence insights with our platform, enabling government security forces to quickly identify and score the network, identity, technology and geographical risks within their ecosystem using Platform-as-a-Service (PaaS) concept.”
Uniquely positioned to provide real-time, contextualized threat intelligence, Resecurity exhibited its latest research, risk management and security capabilities that protect organizations on multiple levels, including network, cloud, applications, and users. The innovative cyber threat intelligence platform combines several tools, allowing administrators to reduce potential blind spots and security gaps by quickly seeing in-depth analysis and specific artifacts obtained through the dark web, botnets activity, network intelligence and high-quality threat intelligence data.
Held May 18-20, 2022, MILIPOL Asia-Pacific is the largest homeland security event in the Asia Pacific. The event was fully endorsed by the Ministry of Home Affairs, Singapore and the Ministry of the Interior of France and welcomed speakers from the United Nations Office on Drugs and Crime (UNODC), ASEANAPOL, World Customs Organization (WCO) and INTERPOL.
To learn more about Resecurity’s cyber risk management and threat intelligence solutions exhibited at MILIPOL Asia-Pacific, visit https://resecurity.com.
Resecurity is a cybersecurity company that delivers a unified platform for endpoint protection, risk management, and cyber threat intelligence. Known for providing best-of-breed data-driven intelligence solutions, Resecurity’s services and platforms focus on early-warning identification of data breaches and comprehensive protection against cybersecurity risks. Founded in 2016, it has been globally recognized as one of the world’s most innovative cybersecurity companies with the sole mission of enabling organizations to combat cyber threats regardless of how sophisticated they are. Most recently, Resecurity was named as one of the Top 10 fastest-growing private cybersecurity companies in Los Angeles, California by Inc. Magazine. An Official Member of Infragard, AFCEA, NDIA, SIA and FS-ISAC. To learn more about Resecurity, visit https://resecurity.com.
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