1673434981
The dependency of the world on new technologies is increasing day by day. AI is the prime candidate for consideration innovation of new applications and approaches to take the advancement to the next level.
Implementing AI in appliances and services has resulted in a more accessible and convenient life for many people. The applications range from smart home devices to mobile phones, toys, and machinery.
AI promises a lot of advantages or benefits to keep the business competitive and drive business value faster with effective processes, as well as to reduce the operation cost significantly. Similarly, a concept arises, AI TRiSM, which marks the systems' reliability, trustworthiness, and security. Let’s discuss it in detail.
AI TRiSM, or Artificial Intelligence Trust, Risk, and Security Management, is a discipline or a framework that supports and enables AI Model governance, reliability, fairness, efficacy, privacy, data protection, and trustworthiness.
Gartner predicted AI TRiSM to be a trending technology in the upcoming years. By 2026, the organization that will incorporate AI transparency, trust, and security will see a 50% efficiency increase in their AI Model in terms of adoption, business goals, and user acceptance.
Also, by 2028, Gartner predicts that AI will handle about 20% workload, and 40% of the economy will be produced by AI and Automation approaches. AI TRiSM has Three Frameworks, named as:
It works to enable Trust, Risk, and Security Management and hold capabilities to anticipate better business outcomes for AI Projects. The main frameworks that are followed for better reliability, security, and trustworthiness are:
This framework is associated with transparency or explainability, i.e., the ability to identify if the model achieved the desired outcomes with steps. This helps build trust and transparency.
Applying precise and strict governance in managing the Enterprise AI risks. Recording and Managing the development and process stages of the models and checking all parts of the release process to check the integrity and compliance.
Ensuring Security at each stage of the process in the ML Model operations. AI Security Management is capable of getting access to the entire ML pipeline, identifying anomalies, automating the CI/CD Pipeline, and scanning vulnerabilities.
It is protecting the AI models and their functionality and helping generate better business outcomes with technological advancements and better adoption strategies.
There are 5 Basic Pillars of it, which hold the foundation of the AI Trust, Risk, and Security Management concept:-
Explainability is the concept of marking every possible step to identify and monitor the states and processes of the ML Models. Simply put, the capability to detect or identify if the model has reached the target.
With this, organizations can monitor the performance of their AI models and propose improvements to make the process more efficient and generate better results with improved productivity.
ModelOps focuses on maintaining and managing the end-to-end lifecycle of every AI Model, including models based on analytics, knowledge graphs, decisioning, etc.
As the name implies, this pillar focuses on detecting and identifying issues and helps AI practitioners see the full image of the Data issues to make effective decisions.
Adversarial Attacks are AI attacks or threats that use data to disrupt Machine learning algorithms and alter the machine learning models' functionality. It detects and remediates these threats to ensure a streamlined process throughout.
The primary fuel source for machine learning models is data, so the better the data is secured, the better the operations and functionality there can be.
AI TRiSM ensures that there is preferred privacy and security of the data to stay in compliance with the regulations for data protection, such as GDPR.
As it provides high transparency, security, and reliability to operations, most organizations are ready to adopt this approach. They want to gain a competitive edge over other companies or industries. There are three basic steps to adopting AI TRiSM methodology:-
With technological advancements, AI is being used everywhere, and the complexity of operations is also increasing. So, proper documentation of the process or the operations provides transparency and enables the monitoring and auditing of events when something goes wrong.
The main reason can be the vast amount of data for the models to operate, as errors are noted when handling exceptional amounts of data. A documentation system can mitigate these errors. It shares its capabilities with industry leaders and data practitioners to formulate an approach and provide an overarching solution to support the technologies.
Checking the systems can enable an organization to prevent breakdowns and improper functionality of the ML models. Checking biases and correcting them to let the model make informed decisions and optimize the processes is preferred.
Checking the situations and alerting to mitigate the issues is something to be focused on to implement AI TRiSM.
The most challenging part of AI is that it still needs more consumer trust. The decision-making capabilities of AI are likely to be questioned because it happens all in the back. Providing transparency and the process structure can help consumers build trust in AI and let it be implemented to improve customer experience and make them comfortable using AI for their daily tasks.
Although helping optimize processes and modernize the approaches for most industries and direct customers, AI still faces some challenges. Let’s discuss some key concerns of AI adoption:-
AI will automate and revolutionize most industries in the upcoming years. Industries lacking the courage to adopt AI will likely fall in the next 5 years. AI is said to provide a platform to grow, drive business value, and help operate the business with utmost efficiency and accuracy. Also, AI TRiSM improves business capabilities by optimizing IT systems for reliability and better data-driven decision-making processes.
Original article source at: https://www.xenonstack.com/
1595491178
The electric scooter revolution has caught on super-fast taking many cities across the globe by storm. eScooters, a renovated version of old-school scooters now turned into electric vehicles are an environmentally friendly solution to current on-demand commute problems. They work on engines, like cars, enabling short traveling distances without hassle. The result is that these groundbreaking electric machines can now provide faster transport for less — cheaper than Uber and faster than Metro.
Since they are durable, fast, easy to operate and maintain, and are more convenient to park compared to four-wheelers, the eScooters trend has and continues to spike interest as a promising growth area. Several companies and universities are increasingly setting up shop to provide eScooter services realizing a would-be profitable business model and a ready customer base that is university students or residents in need of faster and cheap travel going about their business in school, town, and other surrounding areas.
In many countries including the U.S., Canada, Mexico, U.K., Germany, France, China, Japan, India, Brazil and Mexico and more, a growing number of eScooter users both locals and tourists can now be seen effortlessly passing lines of drivers stuck in the endless and unmoving traffic.
A recent report by McKinsey revealed that the E-Scooter industry will be worth― $200 billion to $300 billion in the United States, $100 billion to $150 billion in Europe, and $30 billion to $50 billion in China in 2030. The e-Scooter revenue model will also spike and is projected to rise by more than 20% amounting to approximately $5 billion.
And, with a necessity to move people away from high carbon prints, traffic and congestion issues brought about by car-centric transport systems in cities, more and more city planners are developing more bike/scooter lanes and adopting zero-emission plans. This is the force behind the booming electric scooter market and the numbers will only go higher and higher.
Companies that have taken advantage of the growing eScooter trend develop an appthat allows them to provide efficient eScooter services. Such an app enables them to be able to locate bike pick-up and drop points through fully integrated google maps.
It’s clear that e scooters will increasingly become more common and the e-scooter business model will continue to grab the attention of manufacturers, investors, entrepreneurs. All this should go ahead with a quest to know what are some of the best electric bikes in the market especially for anyone who would want to get started in the electric bikes/scooters rental business.
We have done a comprehensive list of the best electric bikes! Each bike has been reviewed in depth and includes a full list of specs and a photo.
https://www.kickstarter.com/projects/enkicycles/billy-were-redefining-joyrides
To start us off is the Billy eBike, a powerful go-anywhere urban electric bike that’s specially designed to offer an exciting ride like no other whether you want to ride to the grocery store, cafe, work or school. The Billy eBike comes in 4 color options – Billy Blue, Polished aluminium, Artic white, and Stealth black.
Price: $2490
Available countries
Available in the USA, Europe, Asia, South Africa and Australia.This item ships from the USA. Buyers are therefore responsible for any taxes and/or customs duties incurred once it arrives in your country.
Features
Specifications
Why Should You Buy This?
**Who Should Ride Billy? **
Both new and experienced riders
**Where to Buy? **Local distributors or ships from the USA.
Featuring a sleek and lightweight aluminum frame design, the 200-Series ebike takes your riding experience to greater heights. Available in both black and white this ebike comes with a connected app, which allows you to plan activities, map distances and routes while also allowing connections with fellow riders.
Price: $2099.00
Available countries
The Genze 200 series e-Bike is available at GenZe retail locations across the U.S or online via GenZe.com website. Customers from outside the US can ship the product while incurring the relevant charges.
Features
Specifications
https://ebikestore.com/shop/norco-vlt-s2/
The Norco VLT S2 is a front suspension e-Bike with solid components alongside the reliable Bosch Performance Line Power systems that offer precise pedal assistance during any riding situation.
Price: $2,699.00
Available countries
This item is available via the various Norco bikes international distributors.
Features
Specifications
http://www.bodoevs.com/bodoev/products_show.asp?product_id=13
Manufactured by Bodo Vehicle Group Limited, the Bodo EV is specially designed for strong power and extraordinary long service to facilitate super amazing rides. The Bodo Vehicle Company is a striking top in electric vehicles brand field in China and across the globe. Their Bodo EV will no doubt provide your riders with high-level riding satisfaction owing to its high-quality design, strength, breaking stability and speed.
Price: $799
Available countries
This item ships from China with buyers bearing the shipping costs and other variables prior to delivery.
Features
Specifications
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1624699320
Chatbots have been advancing for a few years and have already been widely embraced. By growing the development of chat apps with the emergence of digital technologies and artificial intelligence, they are introducing a new way for companies to connect with the world and, most importantly, with their customers.
…
#chatbots #latest news #learn all about benefits and challenges of ai chatbots for your business #ai chatbots #benefits and challenges #business
1673434981
The dependency of the world on new technologies is increasing day by day. AI is the prime candidate for consideration innovation of new applications and approaches to take the advancement to the next level.
Implementing AI in appliances and services has resulted in a more accessible and convenient life for many people. The applications range from smart home devices to mobile phones, toys, and machinery.
AI promises a lot of advantages or benefits to keep the business competitive and drive business value faster with effective processes, as well as to reduce the operation cost significantly. Similarly, a concept arises, AI TRiSM, which marks the systems' reliability, trustworthiness, and security. Let’s discuss it in detail.
AI TRiSM, or Artificial Intelligence Trust, Risk, and Security Management, is a discipline or a framework that supports and enables AI Model governance, reliability, fairness, efficacy, privacy, data protection, and trustworthiness.
Gartner predicted AI TRiSM to be a trending technology in the upcoming years. By 2026, the organization that will incorporate AI transparency, trust, and security will see a 50% efficiency increase in their AI Model in terms of adoption, business goals, and user acceptance.
Also, by 2028, Gartner predicts that AI will handle about 20% workload, and 40% of the economy will be produced by AI and Automation approaches. AI TRiSM has Three Frameworks, named as:
It works to enable Trust, Risk, and Security Management and hold capabilities to anticipate better business outcomes for AI Projects. The main frameworks that are followed for better reliability, security, and trustworthiness are:
This framework is associated with transparency or explainability, i.e., the ability to identify if the model achieved the desired outcomes with steps. This helps build trust and transparency.
Applying precise and strict governance in managing the Enterprise AI risks. Recording and Managing the development and process stages of the models and checking all parts of the release process to check the integrity and compliance.
Ensuring Security at each stage of the process in the ML Model operations. AI Security Management is capable of getting access to the entire ML pipeline, identifying anomalies, automating the CI/CD Pipeline, and scanning vulnerabilities.
It is protecting the AI models and their functionality and helping generate better business outcomes with technological advancements and better adoption strategies.
There are 5 Basic Pillars of it, which hold the foundation of the AI Trust, Risk, and Security Management concept:-
Explainability is the concept of marking every possible step to identify and monitor the states and processes of the ML Models. Simply put, the capability to detect or identify if the model has reached the target.
With this, organizations can monitor the performance of their AI models and propose improvements to make the process more efficient and generate better results with improved productivity.
ModelOps focuses on maintaining and managing the end-to-end lifecycle of every AI Model, including models based on analytics, knowledge graphs, decisioning, etc.
As the name implies, this pillar focuses on detecting and identifying issues and helps AI practitioners see the full image of the Data issues to make effective decisions.
Adversarial Attacks are AI attacks or threats that use data to disrupt Machine learning algorithms and alter the machine learning models' functionality. It detects and remediates these threats to ensure a streamlined process throughout.
The primary fuel source for machine learning models is data, so the better the data is secured, the better the operations and functionality there can be.
AI TRiSM ensures that there is preferred privacy and security of the data to stay in compliance with the regulations for data protection, such as GDPR.
As it provides high transparency, security, and reliability to operations, most organizations are ready to adopt this approach. They want to gain a competitive edge over other companies or industries. There are three basic steps to adopting AI TRiSM methodology:-
With technological advancements, AI is being used everywhere, and the complexity of operations is also increasing. So, proper documentation of the process or the operations provides transparency and enables the monitoring and auditing of events when something goes wrong.
The main reason can be the vast amount of data for the models to operate, as errors are noted when handling exceptional amounts of data. A documentation system can mitigate these errors. It shares its capabilities with industry leaders and data practitioners to formulate an approach and provide an overarching solution to support the technologies.
Checking the systems can enable an organization to prevent breakdowns and improper functionality of the ML models. Checking biases and correcting them to let the model make informed decisions and optimize the processes is preferred.
Checking the situations and alerting to mitigate the issues is something to be focused on to implement AI TRiSM.
The most challenging part of AI is that it still needs more consumer trust. The decision-making capabilities of AI are likely to be questioned because it happens all in the back. Providing transparency and the process structure can help consumers build trust in AI and let it be implemented to improve customer experience and make them comfortable using AI for their daily tasks.
Although helping optimize processes and modernize the approaches for most industries and direct customers, AI still faces some challenges. Let’s discuss some key concerns of AI adoption:-
AI will automate and revolutionize most industries in the upcoming years. Industries lacking the courage to adopt AI will likely fall in the next 5 years. AI is said to provide a platform to grow, drive business value, and help operate the business with utmost efficiency and accuracy. Also, AI TRiSM improves business capabilities by optimizing IT systems for reliability and better data-driven decision-making processes.
Original article source at: https://www.xenonstack.com/
1598606037
Every week we bring to you the best AI research papers, articles and videos that we have found interesting, cool or simply weird that week.
#ai #this week in ai #ai application #ai news #artificaial inteligance #artificial intelligence #artificial neural networks #deep learning #machine learning #this week in ai
1595398860
Every week we bring to you the best AI research papers, articles and videos that we have found interesting, cool or simply weird that week.Have fun!
#ai #this week in ai #ai application #ai news #artificaial inteligance #artificial intelligence #artificial neural networks #deep learning #machine learning #this week in ai