March 7, 2025|11:26 am
Artificial Intelligence and Machine Learning
Embracing Artificial Intelligence and Machine Learning
Now, advances in machine learning have transformed various vital sectors like technology, transportation, health, finance, science/research and even the military. Researchers studying AI and ML believe, that by 2053, there is a 50% chance of AI outperforming humans in all tasks in 45 years and of automating all human jobs in 120 years.
As the year 2021 embarks upon us, its important to look into major trends in AI and ML so that your business has the competitive edge in a hyper-competitive market. The diversity of the applications of AI and ML have paved the way for innovation and new opportunities for businesses around the world. Revenue generated by AI hardware, software and services was expected to reach $156.5 billion worldwide in 2020, according to market researcher IDC, up 12.3 percent from 2019.
AI will outperform humans in all tasks in 45 years – Cornell University study: When Will AI Exceed Human Performance? Evidence from AI Experts
Here are some major trends businesses can capitalize on:
Re-imagining the Cloud
With enterprises rapidly migrating to the cloud to improve services, improve data management efficiency, streamlining operations and delivering substantial ROI has made the possibilities endless. Major sectors like finance and healthcare, have now realized the capability of AI to analyze and anticipate issues while providing them support to address the challenges faced due to the COVID-19 pandemic, in the year 2020.
The Practicality of AI
Though initially AI was not about practicality, it has gradually evolved to focus more on problem solving. With AI’s capability to seamlessly transition into any sector, it has become an integral part of ‘business-intelligent’ applications. The unassuming nature of AI can process huge amounts of data, recognize the problem, research solutions and provide support during the crucial decision-making process.
Prepping for the ‘Big Data Explosion’
The increased use of IoT devices that seamlessly communicate with each other at rapid speeds, along with the introduction of new technologies like 5G and 6G, will increase the capabilities of AI, tenfold. According to a survey by Deloitte, 74% of AI adopters agree that AI will be integrated into all enterprise applications within three years. AI will enable these apps, and the devices that incorporate them, to generate new services, new insights, and deeper kinds of knowledge. AI and ML are more trustworthy than ever
Due to the pandemic, many enterprises and businesses adopted AI and ML to overcome the challenges that came while operating their workforce remotely. Businesses now have the confidence to keep their workforce online while maximizing their potential and increasing efficiency in resolving challenges on the go. Improved and more accurate forecasting
Despite the unprecedented pandemic situation, huge amounts of data regarding the virus spread was collected, organized and processed on a global scale. AI tools have been instrumental in processing the highly sophisticated data models while, enabling health-officials to predict, plan and execute their strategies to battle the pandemic.
RECENT BLOG
Failure modes and rate of failure
Even though this all started with latency injection as in Yan Cui’s articles, latency is far from the only possible failure we can have in our serverless applications. In failure-lambda, failure-azurefunctions and failure-cloudfunctions there are now five different failure modes to choose from:
Identify Weaknesses
Injects latency to the executed function, controlled using a minimum and maximum span of milliseconds. This can for example be used to simulate service latency or to test and help set your timeout values.
Exception
Throws an exception in the function. Helps you test how your application and code handles exceptions.
Status code
Your function will return a status code of choice, for instance 502 or 404 instead of the normal 200. This gives you the possibility to test what happens when there are errors.
Disk space
Will fill your temporary disk with files to create a failure. If you’re using disk to store temporary files you can test how your application behaves if that disk gets full or you are unable to store to it.
Blacklist (courtesy of Jason Barto)
Blocks connections to specified hosts. Use to simulate services or third parties being unavailable.
All these failure modes can be used together with a rate of failure that you set. The default is to inject failure on every invocation but in reality, it is likely that for example a third party is unavailable on 50% of the calls made to that host or that an exception is thrown on a quarter of the invocations. Setting rate will allow you to achieve this.
