Category Archives: Data Mining
Appian – where AI meets RPA and Process Mining – Diginomica
(Image sourced via Appian )
Last week, Appianheld its annual user conference in San Diego. The event reflected the growing size of Appian and a number of changes (notably AI) impacting buyers AND sellers of software.
Attendance was pegged at over 1500 people on-site and many more virtually. The company, by the way, is approximately twice as big as it was in 2019. The last Appian World I attended in person was in May 2013 and was a fraction of the size (and number of sessions) as this event. See this event writeup of that show for contrast and technology themes.
The name badges this year were interesting to read. I saw lots of developers and partners. But there were also people with Knowledge Management, Process Improvement and other job titles that are often scarce at ERP shows. I also met with a number of partner firm personnel. Appian, by dint of its large customers and their complex processes, is apparently a vendor that large integrators, consultants, process improvement specialists, etc. find attractive.
Complexity is something Appian customers possess. There were numerous demonstrations and breakout sessions whose speakers came from federal government agencies, insurance firms, life sciences and other entities with long, complex processes. These Appian customers and prospects are not satisfied with inordinately slow, potentially error-prone and partially manual processes. These businesses want better processes to improve the customer (or user) experience, reduce costs, increase productivity, and/or gain competitive advantage.
This was also a show where Appian developers and super-users at customers are highly revered. There was a $10,000 prize to the super-developer who won Appians version of a hackathon (i.e., the Live Build Challenge). Even the PR team felt I needed to meet with the lead cheerleader of the developer nation at Appian (It was a pleasure to do so, by the way).
Appian is now branding itself as the End to End Process Platform. This branding reflects their use of new AI/ML/Large Language Model technologies with RPA (robotic process automation) and process mining to solve complex business process challenges quicker than ever. Watching demonstrations of these combo capabilities make me think that Appians toolset is really a Business Productivity Generator. Im not trying to start a branding war with that remark but I think its important for prospective Appian customers to see the company as more than a tools provisioner and more of a firm that helps move organizations to a new level of performance. In my experience, people buy outcomes not tools.
AI as my co-pilot came up in numerous executive one-on-ones, keynotes, etc. Appian executives wanted all of their developer community to realize that newer AI, low code, process mapping, etc. tools will not lead to mass layoffs of programmers/developers. We saw several demonstrations where:
I believe that humans will want to and need to work with these tools. Im good with that concept. What I wonder though is what next years Appian World event is going to look like. I suspect in the next 12 months Appian and its customers will create a form factor larger number of process insights, automations, etc. and there wont be near enough time at the show to highlight even a small percentage of what will likely be some outstanding new creations.
The Data Fabric is what Appian calls its ability to not just stitch together disparate data but to also see how this information is (or could be) used in a process. Process performance and usage statistics are identified via process mining technology. Data is analyzed to see what information is being used in different processes and process steps. The Data Fabric helps companies:
Process HQ is Appians long-range vision of process mining. The technology provides a nice graphical view of a process, statistics from process mining technology, workflow logic, process mining insights, etc. The software then shows where new effort/programming is needed to improve the business rules and outcomes.
One of the more interesting aspects of this capability is that users can see before and after process results/performance statistics to see if bottlenecks, throughput, etc. actually improved and are now at acceptable levels.
Earlier in my career, the process documentation tools I used (not the advanced process automation tools of today) were so limited as to what they could do. In fact, most of these were static documentation tools. Process HQs power comes from harnessing the data within and generated by several Appian technologies to rapidly focus process experts on potential improvements and complete these improvements in short order.
Process Automation/Robotic Process Automation generally includes a number of tools to identify process workflows, exception logic/rules, approvals, etc. An RPA outcome can be a highly automated process where a number of routing, processing, decisions and other actions are occurring automatically. Done well, these tools can dramatically reduce human effort and errors.
There were a number of breakouts where customers, partner firms and/or Appian team members stepped attendees through the effort required to light up their government procurement, insurance underwriting or other complex process. But complexity was only one factor common to many of these presentations. Some processes also have a significant amount of regulation, lots of changes over time, rapidly evolving products, etc.
Where one customer might put dealing with frequently changing regulations as the key driver for using these tools, another customer might list improving customer experience as the top goal. The variability in the kinds of processes being automated was quite noticeable but you could see how each was a critical issue for the company to improve.
In the end though, I did observe that Appian has obviously had a lot of success within the government sector just because of the sessions offered and executive comments. This makes sense as US federal agencies are large, highly regulated entities that would benefit from these tools. Insurance is also another sector with similar challenges. These market & process realities shape Appians go-to-market efforts and reflect the kinds of organizations they target for new deals.
Private AI is not a military person but was a term that was used frequently by Appian executives. Appian has delineated all of the new AI/ML/LLM capabilities into two camps (i.e., public and private) based on where the training data and processing logic for these tools lives. For example, if you want to translate all of your English-language support documentation to Castilian Spanish via a large language model, you might use one of the externally available AI tools to do so. Doing so would mean using a public AI tool and exposing your data to the third-partys tool. That third-party tool will get smarter because of its intake of your firms proprietary data.
If the proprietary data is something of a competitive advantage for your firm, is something that should be held to a high degree of confidentiality, etc., a firm would be better off using its own Private AI tool. There may be other reasons to use a Private AI solution. For example, a planning tool might better understand some financial results if it only uses your own firms sales data. Your firms sales may be countercyclical to those of some of your competitors. Since these tools look for patterns within the chosen datasets, getting great data will help ensure better results. Alternatively, poor, confusing data will simply generate low-value results (i.e., garbage in, garbage out).
Appian executives stated their intent to back Private AI solutions for the foreseeable future. That response, while conservative, will help protect their customers data, confidences, etc. While some public AI use cases were mentioned, it was always with the caveat that this would have to be something where data security could be ensured, the risks to people/companies was minimal, and, Appian had time to thoroughly vet the solution.
New AI Use Cases were popping up throughout the show. Heres a taste of what was being discussed:
Integrator/Partner interest was keen at this show. Most major global service firms had some presence. Accenture was noted for their buildout of innovation factories using Appian technology. RSM was acknowledged for doubling their Appian staff complement over the last year. Many customer presenters were either introduced by or shared speaking duties with their implement/development partner.
Unique Solutions are the stars of this show.
Shows like this, especially when tech is undergoing a shockwave of introspection and change, are fascinating to attend. All kinds of new ideas and concepts are flying about with varying degrees of stickiness. Some attendees will be real short-term thinkers and regardless of the new AI buzz are simply looking for an incremental tool to take home with them. Others are looking for the long-range structural changes on the horizon and how these will affect their industry (and not just their firm or a single process). Both kinds of users/buyers were in attendance.
This show also highlighted for me how far both Appian and the process technology spaces have changed in the last few years. A few years ago, the focus was largely around workflow technology and low code solutions. This show was about process mining, generative AI and more. Evolution is an interesting animal to study.
Finally, the mood at the show was notable. Energy/enthusiasm within the customers, Appian team members, partners, etc. was high. Itll be interesting to see if Appian can maintain this at next years event in Washington D.C.
See also: Appian Platform for Process Automation -Low-Code - Process Mining from May 2021
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Hut 8 Reports Operating and Financial Results for Q1 2023 USA … – PR Newswire
Quarterly revenue of $19.0 million including $4.5 million from the high performance computing business
9,133 self-mined Bitcoin held in custody on March 31
TORONTO, May 11, 2023 /PRNewswire/ -- Hut 8 Mining Corp. (Nasdaq: HUT) (TSX: HUT) ("Hut 8" or the "Company"), one of North America's largest, innovation-focused digital asset mining pioneers,and high performance computing infrastructure provider, is pleased to announce its financial results for the quarter ended March 31, 2023 ("Q1 2023"). All dollar figures are in Canadian Dollars ("CAD"), unless otherwise stated.
"In early 2023, we experienced a confluence of events: electrical issues at our Drumheller site caused equipment failures, while fluctuating energy prices and increased network difficulty affected our mining operations," said Jaime Leverton, CEO of Hut 8. "We also reached an all-time operational high of 1.72 EH/s at our Medicine Hat facility and announced a merger of equals with USBTC, and since then have made progress on key regulatory files required to complete the transaction."
"We continued to strategically manage our finances in Q1 while addressing challenges at the Drumheller site," said Shenif Visram, CFO. "Although we continue to see good client demand in our high performance computing business, the issues on the mining side of the business reflect a decrease in revenue and Bitcoin mined, which the entire leadership and operations team is proactively working to resolve."
"Leading up to the halving, we will continue to focus on strategically increasing our stack of Bitcoin and growing our HPC business including exploring opportunities in the growing Artificial Intelligence market," said Jaime. "We expect that our proposed business combination with USBTC will increase our installed self-mining hashrate to 7.02 EH/s, enhance our geographic reach into new energy markets, and further diversify our lines of business with capex-light, scalable, fiat-based revenue streams, positively distinguishing us from pureplay digital asset miners, who post-halving, are likely to have more exposure to diminishing returns driven by an increasing global hashrate and additional competition from sovereign nations and well-funded new entrants."
Q1 2023 HIGHLIGHTS
BITCOIN INVENTORY AND VALUE
As at March 31, 2023, the Company had a total self-mined, unencumbered, and custodied Bitcoin balance of 9,133 with a market value of $352.0 million. During the first quarter of 2023, 475 Bitcoin were mined and 428 Bitcoin were sold, for which the Company received proceeds of $14.5 million.
OPERATING AND FINANCIAL OVERVIEW
For the three months ended March 31
Three Months Ended
(CAD thousands, except per share amounts)
2023
2022
Operating results
Digital assets mined
475
942
Financial results
Total revenue
$ 19,021
$ 53,333
Net income
108,503
55,708
Mining Profit (i)
2,590
32,906
Adjusted EBITDA (i)
(3,697)
27,109
Per share
Net income - basic
$ 0.49
$ 0.33
Net income - diluted
$ 0.47
$ 0.31
(i) Non-IFRS measure - see "Non-IFRS Measures" section below. Certain comparative figures have been restated where necessary to conform with current period presentation.
As at
(CAD thousands)
March 31,2023
December 31,2022
Financial position
Cash
$ 15,904
$ 30,515
Total digital assets
352,436
203,627
Total assets
541,453
412,937
Total liabilities
70,811
61,547
Total shareholders' equity
470,642
351,390
Working Capital (ii)
339,855
215,490
(ii) Calculated as current assets less current liabilities.
For more information, please refer to the Company's management's discussion & analysis (the "MD&A") and the Company's unaudited condensed consolidated interim financial statements for the three months ended March 31, 2023 and 2022. These documents are available on the Company's website at hut8.io, under the Company's SEDAR profile at http://www.sedar.com, and under the Company's EDGAR profile at http://www.sec.gov.
______________________________
(i)Non-IFRS measure - see "Non-IFRS Measures" section below. Certain comparative figures have been restated where necessary to conform with current period presentation.
NON-IFRS MEASURES
This press release makes reference to certain measures that are not recognized under IFRS and do not have a standardized meaning prescribed by IFRS. They are therefore not necessarily comparable to similar measures presented by other companies. The Company uses non-IFRS measures including "Mining Profit" and "Adjusted EBITDA" as additional information to complement IFRS measures by providing further understanding of the Company's results of operations from Management's perspective and should not be viewed as alternatives to, or replacements of, measures of operating results and liquidity presented in accordance with IFRS.
The following tables and definitions reconcile non-IFRS measures used by the Company to analyze the operational performance of Hut 8 to their nearest IFRS measure and should be read in conjunction with the Company's unaudited condensed consolidated interim financial statements for the three months ended March 31, 2023 and 2022.
Mining Profit
"Mining Profit"represents gross profit (revenue less cost of revenue), excluding depreciation and revenue and site operating costs directly attributable to hosting services and high performance computing operations. Mining Profit shows profitability of the Company's core digital asset mining operation, without the impact of non-cash depreciation expense. Mining Profit measure provides investors the ability to assess the profitability of the mining operations exclusive of general and administrative expenses.
The following table reconciles gross (loss) profit to our non-IFRS measure, Mining Profit:
For the three months ended March 31
2023
2022
Gross (loss) profit
$ (6,207)
$ 16,455
Add (deduct):
Revenue from hosting
(751)
Revenue from high performance computing
(4,495)
(3,290)
Site operating costs attributable to hosting and high performance computing
2,433
2,127
Depreciation
10,859
18,365
Mining Profit
$ 2,590
$ 32,906
Adjusted EBITDA
"Adjusted EBITDA"represents EBITDA (net income or loss excluding net finance income or expense, income tax or recovery, depreciation, and amortization) adjusted to exclude non-cash share-based compensation, fair value gain or loss on revaluation of digital assets and warrants, non-recurring impairment charges or reversals of impairment, and costs associated with one-time or non-recurring transactions. Adjusted EBITDA is used to assess profitability without the impact of non-cash accounting policies, capital structure, taxation, and one-time or non-recurring transactions. This performance measure provides a consistent comparable metric for profitability of the Company across time periods.
The following table reconciles net income to our non-IFRS measure, Adjusted EBITDA:
For the three months ended March 31
2023
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Hut 8 Reports Operating and Financial Results for Q1 2023 USA ... - PR Newswire
Allied Energy Corp Provides Update on the Thiel Well Bitcoin Mining Project with Enerhash – Yahoo Finance
Carrollton, Texas, --News Direct-- Allied Energy Corporation
Allied Energy Corp (OTC: AGYP), a producing oil and gas company focused on the leasing and reworking of oil and gas reserves in one of the most prolific hydrocarbon area in the United States, is pleased to provide a shareholder update regarding the Company's activities partnering with Enerhash USA at the Thiel Well site in an effort to begin flare gas bitcoin mining.
On April 26th, CEO George Monteith of Allied Energy received a revised field build out report distributed by Enerhash's personal.
Due to circumstances beyond the Company's control, initial target dates for the Thiel site had to be adjusted. At this time the Company is confident that all challenges have been overcome regarding the initial delays. The Company is pleased with the revised timeline and is thankful to report that thus far everything is proceeding according to plan. To date the following work has been completed:
Operating permits - completed
Site survey - completed
Site planning - completed
Elevation study - completed
Contractor proposal for site buildout - completed
Allied will update their shareholders as further developments occur with press releases and media updates on Twitter.
The initial Thiel project, if all goes as planned, is expected to take 8-10 weeks to complete. The generators and data centers will be located 150 feet south of the wellhead. A meter run will be installed just north of the generator pad. The existing water tank will be reused for discharge from the separator. The elevated pad will be constructed of compacted engineered fill to support generator weights up to 60,000 lbs. per generator and 20,000 lbs. per data center. A reinforced concrete pad will be constructed on top of the compacted engineered fill to support the generator / generators. The contractor will provide two 3-inch electrical conduits with sweeping connections from the generators to each data center pad.
Story continues
Allied CEO George Monteith commented: "The Thiel is the first location where Allied will establish a bitcoin mining footprint in partnership with Enerhash. At this time, we believe that the Thiel site will be a 3-megawatt center and power three containers of bitcoin mining equipment. As per our last release investors / current shareholders can see that we are laying a broader foundation of gas well resources through our new partnership with Sloan Petroleum. Ultimately, we are focused on completing the initial 20-megawatt project with Enerhash to then set our sights toward completion of the 100-megawatt project. I am appreciative of all the hard work my team has given, we have a detailed plan and the resources to make it happen, now it is time to make the push toward mining digital currency."
About Enerhash:
Enerhash is an energy technology and digital infrastructure development company founded by European energy experts in 2019. Enerhash has developed projects on three continents providing renewable energy optimization and grid balancing services including New Zealand, Sweden, Hungary and now they are entering into the USA.
Enerhash USA will align with energy producers as a solution to help alleviate harmful methane emissions caused by production. These solutions will monetize wasted natural gas resources to reduce emissions by eliminating routine flaring to reach ESG goals and unlock the value from stranded resources. To discover more about Enerhash USA, visit their corporate website at http://www.enerhashusa.com.
About AGYP:
Allied Energy Corp. is an energy development and production company acquiring oil & gas reserves in some of the most prolific hydrocarbon bearing regions of the United States. The Company specializes in the business of reworking & re-completing 'existing' oil & gas wells located in the thousands of mature oil & gas producing fields across the United States. The Company applies its knowledge, experience, and effective well-remediation technologies to achieve higher production volumes, longer well life, and more efficient recovery of the proven and available oil and gas reserves in the fields/projects in which it has acquired an ownership interest. The Company will utilize updated technologies such as hydraulic fracturing ("fracking"), drilling of lateral ("horizontal") legs in productive zones, and utilizing new cased hole electric logging to locate bypassed pays, all to enhance daily rates and oil & gas recoveries. By acquiring interests in a growing number of selected projects in various regions, Allied Energy Corp. is diversifying its exposure and effectively minimizing risk as it pursues corporate growth, top line & bottom-line revenues to the benefit of all stakeholders. There are proven, recoverable reserves contained in the many aging oil & gas fields that have been bypassed by companies moving away from these fields in search of deeper, more plentiful, but more costly reserves. The Company plans to concentrate on bypassed oil and gas as there is less competition and, as mentioned above, the costs are considerably less. Additionally, the company will acquire interests in marginal wells that can be acquired at minimal cost, of which there are 420,000 wells in the U.S. Quoting Barry Russell, President of the Independent Petroleum Association of America ("IPAA") - "With approximately 20 percent of American oil production and 10 percent of American natural gas production coming from marginal wells, they are America's true strategic petroleum reserve."
Safe Harbor Statement:
This Press Release may contain certain forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. The Company has tried, whenever possible, to identify these forward-looking statements using words such as "anticipates," "believes," "estimates," "expects," "plans," "intends," "potential" and similar expressions. These statements reflect the Company's current beliefs and are based upon information currently available to it. Accordingly, such forward-looking statements involve known and unknown risks, uncertainties and other factors which could cause the Company's actual results, performance or achievements to differ materially from those expressed in or implied by such statements. The Company undertakes no obligation to update or advise in the event of any change, addition or alteration to the information catered in this Press Release, including such forward-looking statements.
Contact:
Allied Energy Corporation
Phone: 972-632-2393
Email: info@alliedengycorp.com
Twitter: https://twitter.com/AlliedEnergyCo1
Enerhash USA LLC
Website: http://www.enerhashusa.com
Email: info@enerhash.com
Twitter: https://twitter.com/Enerhash1
Linkedin: https://www.linkedin.com/company/enerhash/
Allied Energy Corporation
+1 972-632-2393
View source version on newsdirect.com: https://newsdirect.com/news/allied-energy-corp-provides-update-on-the-thiel-well-bitcoin-mining-project-with-enerhash-118586261
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AI-powered People Analytics Tool that can change Employee … – TechiExpert.com
Introduction about the founders
Flowace was co-founded in 2017 by brothers Tarun and Varun Kodnani. Tarun did MTech from London and Varun did his undergrad from London too.
We were in a spot of bother when we tried reviving our previous fresh out-of-college venture Cabzo, an app-based taxi service. This eventually led us to create Flowace, a time-tracking and billing management platform that summarizes the duration a user has spent on different work activities.
We felt there was a need to develop a product that could help manage timesheets in an automated way. The formation of Flowace dawned upon us.
The founders, along with the teams dedication and hard work, have bestowed us with the Best Workforce Automation Tool for BPOs Award, at the 11th edition of the BPO Innovation Summit held recently amongst other industry accolades.
Currently, the company is offering four products.
Time tracking and productivity tool can be used for billing and also assessing the cost vs benefit analysis in the organization. Per client, profitability can be tracked once the cost analysis is done and the companies can go to their clients and present the same to either increase the retainers or reduce the scope by which one can improve the overall profitability per client so that the overall profits of the company goes up.
Flowace has helped firms with data management, data mining and keeping a check on productivity. The time management feature has helped clients keep a check on productivity because the software auto-stamps the time itself.
The key features of Flowace are that it automates workflow so that all processes can be easily managed in one place. We are a leading player in developing workforce automation tools in the BPO industry. Our software accurately tracks employee efficiency and helps in re-assigning tasks to increase productivity. It maximizes billable hours and shores up profitability for BPOs.
How do you measure and improve employee productivity?
We are not an employee monitoring or micromanagement tool. We believe in Peter Druckers powerful words You cannot improve what you cant measure. Like how we measure our fitness and weight, its imperative to measure our time consumption at work. Our primary purpose is to Measure, Analyze, Upskill & Grow.
Even though the product was started as a time tracking tool and has eventually moved to productivity which has two more aspects to be added like focus and efficiency. There is a clear proof of improving productivity by 31% in three to six months after implementing Flowace in their organisations, besides saving half an hour on a daily basis by reducing distractions of employees.
This product leads to better appraisal systems in organisations. Underdogs and dark knights are identified in the organisations and can build recognition system for the employees. The companies have started issuing badges to best performers based on the three parameters built in the product like time, focus and efficiency and the employees have started vying for the same on a very competitive level.
Which industry verticals are you currently focusing on?
We started to build the platform for lawyers but realised that this is universal. It could be used by chartered accountants, financial firms and even general firms
The platform has found takers among law, professional services, IT Services, KPOs, BPOs, and CA firms.
Our platform is currently trusted by more than 35,000 users. The clientele includes digite, egis, University Living, codemantra and Function Up, amongst others.
How has been the growth trajectory of Flowace since inception?
Our growth trajectory has always been on an upward curve since our inception.
We have come a long way since our initial investment was Rs. 20 lakh from the family and recently the company raised $ 1.50 million pre-series fund from friends and families.
We believe in complete autonomy for users. Our tool that allows users and employers to track the time spent on different tasks is a testament to that.
Any new products in the pipeline?
The company is currently working on building Engineering Dashboard for IT product companies to integrate all the functions in building products like developer environment, Q and A environment, staging environment and Production environment.
There are many companies offering solutions in individual segments of whole product building environment but none of them have an integrated product that can fast-track the whole product-building process. Our product would provide and integrated SOP for product building by avoiding any conflicts in the whole process to speed up product development.
These are called DORA Metrics. This product is available in the US for the last five years but it is going to be a unique product for the Indian market. Now the market is demanding for this product and we are actively building this product and will launch it soon.
Our vision is to build a global company and take these products to international markets as the biggest market is there. We are currently working with two companies in USA AWS and Ergode.
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AI-powered People Analytics Tool that can change Employee ... - TechiExpert.com
OUR VIEW: The challenge of dealing with AI – Herald & Review
Editorial board
The challenges were facing with the current spate of artificial intelligence are nothing new, even if its particularly more dangerous than previous iterations.
Experts and analysts are pointing to recent AI developments as both revolutionary and challenging.
Changes have been observed in the areas of robotics, computer vision, machine learning and natural language processing. Among the sectors of the economy being transformed by the changes are healthcare, finance, education and transportation.
The advancing sophistication of artificial intelligence programs is alarming. Language model GPT-3 (Generative Pre-trained Transformer 3) produces a text that not just resembles human speech, but also logical and contextually relevant responses to natural language questions.
Computer vision teaches computers to identify and categorize objects, people, and activities in pictures and movies.
People are also reading
Personalized medicine utilizes AI algorithms to create individualized treatment plans based on a patients unique health history and genetic makeup.
A primary concern is the difficulty of mapping how an AI program came to its conclusion. The objective is to create AI systems that are not just precise but also understandable and transparent. Thats part of the reason language model GPT-3 was released as open source.
In the rush to take advantage of these advances, one key factor comes to the fore of the discussion: Ethics. Ethical AI denotes creating and implementing systems that are transparent, accountable and aligned with human values and rights.
That final clause aligned with human values and rights reeks of despair rather than hope. Were unable to agree on very basic human values and rights. Humans have a history of technology outdistancing our tendency toward rash decisions and violence.
Can artificial intelligence be used for evil? It already has been. When we find how much of nefarious nature is going on just under the surface, we can imagine what worse might be going on. Have you or someone you know been part of class-action settlements against unauthorized use of data? Those awards are a way of buying off a public whose personal information has already been and continues to be compromised.
Data mining hasnt stopped and wont stop and is a direct path to changing our lives. Were losing the ability to control how our appearances and thoughts are portrayed. Even if you think these discoveries havent been used nefariously previously, you cant believe its terrors can remain dormant.
Manipulations of words, sounds and images have been accepted forever. We dont blink these days at a meme or a story or a video clip thats been manipulated. Sometimes we laugh, sometimes we get angry, and too often we dont realize the veracity of our source.
If you havent been fooled by something on the internet, its probably because you arent on the internet.
Being fooled by something you see, hear or read is not the worst thing that can happen, especially if you keep an open mind and understand theres a chance youve been fooled. From fake quotes to Photoshop forgeries to holograms of performers living and dead, artificial items have fooled everyone. Be open to possibilities.
Also, learn which entities you can trust. Sources that deserve your confidence havent just appeared out of the air in the last six months.
You know the meme that features a photo of Ian McKellen in costume as Gandalf from The Lord of the Rings accompanied by the (Yoda Star Wars) quote, Do, or do not. There is no try attributed to Dumbledore (from the Harry Potter books)?
Thats a fake. And you dont need to be an expert in AI to understand that.
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OUR VIEW: The challenge of dealing with AI - Herald & Review
Top 10 Career Opportunities To Grab After B.Tech In Computer … – Analytics Insight
B.Tech in Computer Science is one of Indias most popular and sought-after engineering courses. It offers a comprehensive curriculum that covers various aspects of computer science, such as programming, data structures, algorithms, operating systems, networks, databases, artificial intelligence, and more; career opportunities after B.Tech is broad both in India and abroad. They can work in various domains, such as software development, web development, database administration, data science, cloud computing, cybersecurity, and research. This article will explore the top 10 career opportunities after B.Tech in Computer Science. Some of the career opportunities after B.Tech in Computer Science are:
Software Developer: A software developer is responsible for designing, developing, testing, and maintaining software applications or systems that meet the needs and requirements of the clients or users. Software developers use various programming languages, tools, frameworks, and methodologies to create software solutions for different platforms and devices.
Web Developer: A web developer is responsible for creating and maintaining websites or web applications that are accessible and user-friendly on the Internet. To create dynamic and interactive web pages and features, web developers use various web technologies, such as HTML, CSS, JavaScript, PHP, Ruby on Rails, WordPress, and more.
Database Administrator: A database administrator manages and oversees the data stored in databases or data warehouses. Database administrators ensure the data is accurate, secure, consistent, and available for authorized users or applications. Database administrators use various database management systems (DBMS), such as MySQL, Oracle, SQL Server, MongoDB, and more, to create, modify, backup, restore, and optimize databases.
Data Scientist: A data scientist analyzes large and complex data sets to extract meaningful insights and patterns to help decision-making or problem-solving. Data scientists use various data science techniques, such as statistics, machine learning, data mining, data visualization, and more, to process and helpfully present data.
Cloud Computing Professional: A cloud computing professional is responsible for designing, developing, deploying, and managing cloud-based applications or services that run on remote servers over the internet. Professionals use various cloud computing platforms or providers (such as AWS, Azure, Google Cloud, etc.) to create scalable, reliable, cost-effective cloud solutions for different purposes.
Cybersecurity Expert: A cybersecurity expert protects data, systems, networks, and devices from unauthorized access, attacks, or threats. Cybersecurity experts use cybersecurity tools, techniques, standards, and best practices to identify, prevent, detect, respond, and recover from cyber incidents or breaches.
Computer Systems Analyst: A computer systems analyst analyzes an organizations existing computer systems or processes and recommends improvements or solutions to enhance efficiency or performance. Computer systems analysts use various analytical skills, technical skills, communication skills, and business knowledge to understand clients or users needs and goals and design suitable computer systems or solutions for them.
Software Engineer: A software engineer is responsible for applying the principles of software engineering to design, develop, test, and maintain high-quality software products or systems that meet the specifications and standards of the clients or users. Software engineers use various software engineering methodologies (agile, waterfall, etc.) to manage the software development life cycle (SDLC).
Computer Network Architect: A computer network architect is responsible for designing, building, configuring, and maintaining computer networks that enable communication and data transfer among devices or locations. Computer network architects use various network devices (routers, switches, firewalls, etc.) and protocols (such as TCP/IP, Ethernet, Wi-Fi, etc.) to create secure, efficient, and reliable networks.
Computer and Information Research Scientist: A computer and information research scientist is responsible for researching various topics related to computer science or information technology and developing new theories, methods, algorithms, or applications that can advance the field. Computer and information research scientists use various research, creativity, programming, and mathematical skills to explore new problems or challenges and create innovative solutions.
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Top 10 Career Opportunities To Grab After B.Tech In Computer ... - Analytics Insight
Looking for a job in fintech sector? Here are five in-demand skills in the fintech – Economic Times
Fintech has transformed the financial industry by providing innovative solutions for financial services. Over the years, fintech has evolved, offering users a simple, faster, cheaper, and more convenient way of accessing financial services and promoting digital inclusion. From tapping new segments to exploring foreign markets, fintech is supporting multiple aspirations.The fintech sector is continuously growing all over the world, and the trajectory of growth in India has also been on the rise. By 2030, it is projected that the prospective Indian FinTech market will generate $200 billion in revenue. As the sector evolves, the expertise required in it is also increasing, thus demanding the workforce skilled with the required knowledge to help the industry grow.
Need for the latest skills in the fintech industryThe fintech industry is rapidly growing and evolving, and it requires a range of specialized skills to succeed. The sector involves the use of advanced technology such as blockchain, artificial intelligence, and machine learning. To succeed in fintech, one needs to have a strong technical background and a deep understanding of financial markets, products, and services to meet the needs of customers.
Data Analysis: Data analysis is a crucial component of the fintech industry, and data analysts play an essential role in helping fintech companies make informed decisions. Fintech companies generate vast amounts of data, and professionals who can collect, analyze, and interpret this data are in high demand. Data analysts with strong skills in data mining, machine learning, and visualization tools can help fintech companies make informed decisions and gain a competitive edge. Overall, data analysts are essential in the fintech industry, helping companies to leverage data to make informed decisions, manage risks, and gain a competitive advantage.
Artificial Intelligence & Machine Learning: Artificial intelligence (AI) and machine learning (ML) are transforming the fintech industry, enabling companies to automate tasks, improve decision-making, and enhance the customer experience. AI and ML help detect fraudulent activities quickly and accurately. Their algorithms can analyze patterns and anomalies in customer data, transaction history, and other relevant data sources to identify potential fraud and prevent losses.
Cybersecurity: Cybersecurity is of paramount importance in the fintech industry, as companies deal with sensitive financial information and are vulnerable to cyber-attacks. A skilled cybersecurity expert can assess the risks associated with a fintech company's operations and develop strategies to mitigate those risks. They can identify vulnerabilities in the company's infrastructure, software applications, and data storage systems and implement appropriate security measures. In the event of a cyber attack, a cybersecurity expert can respond quickly and effectively to mitigate the damage. They can identify the source of the attack, contain the damage, and prevent future attacks.
The fintech industry has experienced rapid growth in recent years and is expected to continue to expand in the future. As the industry evolves, there is a growing need for skills that can help fintech companies innovate, improve efficiency, and better serve customers. Technical expertise, financial knowledge, analytical skills, problem-solving skills, and communication skills are all essential to develop innovative fintech solutions that meet the needs of customers and disrupt the traditional financial industry.(The writer is Founder and MD, Escrowpay)
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Looking for a job in fintech sector? Here are five in-demand skills in the fintech - Economic Times
Deep Learning Market Poised to Exceed US$ 130667 Million by … – Market Research Blog
The Deep learning neural networks are being used by businesses to mine massive volumes of data for insightful information that can be used to develop new products, enhance consumer experiences, and expand revenue potential for the deep learning market. One of the most cutting-edge technologies in business computing is deep learning, which is growing on a global scale.
During the projected period, the worldwide deep-learning market would expand due to the increasing demand for improved human and system interaction. Deep learning algorithms will help humans become more capable as they provide expert advice. Additionally, deep learning technology is increasingly being used in a variety of industrial sectors, including healthcare, finance, retail, and others. Strong R&D for the development of new products is another element propelling this market.
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The rise of data mining applications in the deep learning market is being driven by the rising need for deep learning in fraud detection, database systems, and cyber security. The patient information, diagnosis, and other data sets produced by the healthcare industries are massive. Data mining is therefore expected to experience the fastest growth rate in the healthcare industry shortly.
Deep Learning Market: Market Dynamics
The rising necessity for hardware platforms with high computing power to execute deep learning algorithms is a driving factor of the Deep Learning market Increasing complexity in hardware due to the complex algorithm in deep learning technology can hamper the growth of the Deep Learning market. Growing usage of deep learning in data analytics and database systems growth opportunities for the Deep Learning Market.
Global Deep Learning Market: Competition Landscape
Few prominent players in Deep Learning market include Google Inc., Microsoft Corporation, Qualcomm Technologies, Inc., IBM Corporation, Intel Corporation, General Vision Inc. and NVIDIA Corporation, etc.
Deep Learning Market: Regional Outlook
North America is prominent and holds the largest share of the deep learning market and is estimated to be in the leading position owing to the widespread adoption of deep learning technology. There is high growth in the deep learning market in North America due to the presence of prominent players in the region that offers deep learning services and hardware such as IBM Corporation, Qualcomm Technologies, Inc. and Intel Corporation, etc. Latin America and MEA are expected to contribute significantly over the forecast period.
The report covers an exhaustive analysis on
Regional analysis of the Global Deep Learning Market includes
North America Deep Learning Market
Latin America Deep Learning Market
Eastern Europe Deep Learning Market
Western Europe Deep Learning Market
Asia Pacific Deep Learning Market
Japan Deep Learning Market
Middle East and Africa Deep Learning Market
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Deep Learning Market Poised to Exceed US$ 130667 Million by ... - Market Research Blog
Natural Language Processing Market to be $262.4 Billion by 2030 … – GlobeNewswire
Redding, California, May 10, 2023 (GLOBE NEWSWIRE) -- According to a new market research report titled, Natural Language Processing Market by Component, Organization Size, Application, Sector (IT & Telecommunications, BFSI, Retail & E-commerce, and Healthcare & Life Sciences) - Global Forecast to 2030, the global natural language processing market is projected to reach $262.4 billion by 2030, at a CAGR of 34.4% from 2023 to 2030.
Natural language processing (NLP) is a form of artificial intelligence (AI) that allows computers to understand human language. NLP offers several benefits for companies across industries, such as enabling non-subject matter experts to find answers to their questions, analyzing data from both structured and unstructured sources, identifying the root causes of business problems, and discovering the most profitable customers and understanding the reasons behind it. Furthermore, it identifies and addresses fraudulent claims and behavior, identifies customer communication patterns and reduces customer complaints, and analyzes and evaluates your competitors product offerings.
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The growth of the natural language processing market is driven by the increased use of smart devices and the growing demand for NLP-based applications for customer support and NLP tools in call centers. Moreover, the rapid adoption of cloud-based technologies and increasing applications of NLP in the healthcare sector provide significant opportunities for the players operating in the global natural language processing market. However, the limitations in developing NLP technology restrain the growth of this market to some extent. Additionally, data privacy & security concerns pose challenges to the growth of the natural language processing market. Besides, virtual assistants & chatbots and the growing demand for speech analytics solutions are the key trends observed in the natural language processing market.
The global natural language processing market is segmented by component {solutions [optical character recognition solutions, interactive voice response systems, autocoding systems, document analytics solutions, speech analytics solutions, simulation & modeling solutions, customer experience management solutions, digital assistants and chatbots, and other NLP solutions (root cause analysis solutions, spam detection solutions, and data mining solutions)], services (professional services, managed services), organization size (small & medium-sized enterprises, large enterprises), application [robotics & automation, smart cities, smart retail, smart healthcare, e-mail filtering, language translation, sentiment analytics, social media analytics, other NLP applications (market intelligence & targeted advertising, and data extraction], sector [IT & telecommunications, BFSI, retail & e-commerce, healthcare & life sciences, transportation & logistics, government & public sector, media & entertainment, manufacturing, education, food & beverages, and other sectors (oil & gas, and automotive)]}. The study also evaluates industry competitors and analyzes the market at regional and country levels.
Based on component, the global natural language processing market is segmented into solutions and services. In 2023, the solutions segment is expected to account for the largest share of the global natural language processing market. The large market share of this segment is attributed to the surge in demand for interactive voice response systems to interact with callers and gather information; rising demand for document analytics solutions for managing a document repository; surge in demand for speech analytics to improve contact center operations; the growing popularity of customer experience management solutions to streamline the customer journey, allowing customers to design, connect, deliver, and manage experiences across diverse channels; and increasing proliferation of digital assistants and chatbots to create conversational experiences for business applications. This segment is also projected to register the highest CAGR during the forecast period.
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Based on organization size, the global natural language processing market is segmented into large enterprises and small and medium-sized enterprises (SMEs). In 2023, the large enterprises segment is expected to account for the larger share of the global natural language processing market. The large market share of this segment is attributed to the growing adoption of NLP solutions by large enterprises to analyze, interpret, and classify a company's raw, unstructured big data collected from different sources like customer reviews, social media listening, and employee forums, and increasing demand for social media analytics and web monitoring solutions in retail & e-commerce sector which allows knowing the customers' insights concerning particular products or services.
However, the small & medium-sized enterprises segment is expected to register the highest CAGR during the forecast period. The growth of this segment is driven by the increasing demand for improved operational efficiency in small customer service environments, the surge in demand for automating interactions to reduce the burden on human call center operators, and the growing proliferation of call recording and speech analytics technology in small organizations.
Based on sector, the global natural language processing market is segmented into IT & telecommunications, BFSI, retail & e-commerce, healthcare & life sciences, transportation & logistics, government & public sector, media & entertainment, manufacturing, education, food & beverages, and other sectors. In 2023, the IT & telecommunications segment is expected to account for the largest share of the global natural language processing market. The large market share of this segment is attributed to the increasing use of NLP tools by telecom companies to solve typical customer problems in an efficient manner and wherever possible without human intervention, the increasing proliferation of digital assistants and chatbots by IT industries, and the need for NLP solutions by telecom companies for categorizing support requests.
However, the healthcare & life sciences segment is projected to register the highest CAGR during the forecast period. The growth of this segment is driven by the increasing need to handle the surge in clinical data, the use of NLP services to identify patients who need improved care, and the growing demand for advanced patient health record systems, managed care, PHM applications, and analytics and reporting.
Based on geography, the global natural language processing market is segmented into North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa. In 2023, North America is expected to account for the largest share of the global natural language processing market. The large share of this market is attributed to the increasing focus on NLP services & solutions developments in North America, the presence of well-established NLP providers such as Microsoft Corporation (U.S.), Oracle Corporation (U.S.), International Business Machine Corporation (U.S.), NVIDIA Corporation (U.S.), Qualcomm Incorporated (U.S.) across the region, the presence of natural language processing startups in the U.S. and Canada, and the use of patient health record systems.
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Furthermore, leading NLP players across the region are putting in efforts to launch AI applications that support NLP capabilities. For instance, in October 2022, International Business Machine Corporation (U.S.) expanded its embeddable AI software portfolio by releasing three new libraries designed to help IBM Ecosystem partners, clients and developers more easily, quickly and cost-effectively build their AI-powered solutions and bring them to market. The AI libraries were developed in IBM Research and designed to provide Independent Software Vendors (ISVs) across industries an easily scalable way to build natural language processing, speech-to-text, and text-to-speech capabilities into applications across any hybrid, multi-cloud environment. Such developments are expected to support the growth of this market.
However, Asia-Pacific is projected to register the highest CAGR during the forecast period. The growth of this market is driven by the increasing smartphone usage across the region, government initiatives for implementing NLP solutions & services in countries such as China, Japan, and India, an increase in the use of smart devices and cloud-based solutions and NLP-based applications to enhance customer service, and technological innovations in the regions healthcare sector.
The key players operating in the global natural language processing market are Google LLC (U.S.), Microsoft Corporation (U.S.), Amazon Web Services, Inc. (a subsidiary of Amazon.com, Inc.) (U.S.), Oracle Corporation (U.S.), International Business Machine Corporation (U.S.), NVIDIA Corporation (U.S.), QUALCOMM Incorporated (U.S.), Baidu, Inc. (China), Verint Systems Inc. (U.S.), SAP SE (Germany), INTEL CORPORATION (U.S.), Adobe Inc. (U.S.), Genpact Limited (U.S.), SAS Institute Inc. (U.S.), and NetBase Solutions, Inc. (U.S.)
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Scope of the Report
Natural Language Processing Market, by Component
Natural Language Processing Market, by Organization Size
Natural Language Processing Market, by Application
Natural Language Processing Market, by Sector
Natural Language Processing Market, by Geography
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Natural Language Processing Market to be $262.4 Billion by 2030 ... - GlobeNewswire
Global Airport Leaders’ Forum urges operators to be future-ready … –
DUBAI, 12th May, 2023 (WAM) Global Airport Leaders Forum, co-located at the 22nd Airport Show, discussed measures to transform security at airports by bringing together leading entities responsible for airport security and plan for the future of aviation security by embracing new technologies.
Suggestions have been made to bridge the communication and collaboration gaps between airports, airlines, government authorities and law enforcement agencies and strengthen the critical lines of communication and initiate cross-party collaboration.
The Forum also urged the industry to share best practices by identifying case studies of effective collaboration in the rest of the world.
New technologies will support different stakeholders in adopting security facilities. We want to make sure that technologies that are adopted are as seamless as possible to ensure safety to passengers, quicker passenger handling to enable more flight operations, air traffic control, ground handling and at the same time more time made available to passengers to spend time at duty free areas that will increase revenue for airport operators, said Abdullah Al Shamsi, Senior Director of Future of Things, Dubai Aviation Engineering Projects (DAEP).
It is very important to maintain balance between passenger experience and security using technology. Airports and airlines should work in tandem to ensure seamless and frictionless travel. With data mining and analytics, it is possible to check what are the peaks and lows and what are the bottlenecks during peak hours and which sectors, said Dr. Majid Alsarrah, Industry Expert and Legal Adviser, UAE.
Passengers benefit from technology, less check-in time, e-gate, RFID technology for efficient baggage handling, improve passenger experience and enhance operational efficiency.
The Airport Security Technology panel urged the industry to leverage AI-driven cyber security solutions, 5G, IoT and facial recognition system to optimize safety and security at airports, and embrace the latest technology to expedite the movement of passengers while maintaining the highest security standards.
Airport operators should understand the importance of viewing passengers as customers and treating their time accordingly. They should invest in technology for digital identity and biometrics for seamless international travel, future-proof body scanners to enhance security measures without compromising on privacy, said Shantanu Gangakhedkar, Senior Consultant, Aerospace & Defense, Frost & Sullivan.
The forum also discussed measures to manage the shortage of skilled labour in aviation.
Airport Show, organised by RX Global, is supported by Dubai Civil Aviation Authority, Dubai Aviation Engineering Projects, Dubai Airports and dnata, and sponsored by ADB Safegate, Smiths Detection and HADID International Services.
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Global Airport Leaders' Forum urges operators to be future-ready ... -