Artificial intelligence (AI) is developing very quickly and it’s no surprise that we’re fascinated by its capabilities. At one end of the spectrum, there’s wide-eyed wonder and excitement – which often leads to criticism – and on the other, you have fears of a dystopian future. We understand the importance of being able to trust AI and for it to be truly beneficial. Microsoft’s approach, which is based on their AI principles, is focused on proactively establishing guardrails for AI systems so that any risks are anticipated and mitigated, and benefits are maximised.
Over the years, there have been a lot of new principles and ideas that have helped shape AI’s development. For example fairness, accountability, transparency and privacy. Generally, these risks are well understood. Furthermore, while principles are necessary, they alone aren’t enough. The hard work begins when you try to turn those principles into practices.
Artificial Intelligence (AI) is a man-made technology in which computers can perform tasks in a manner usually reserved for humans. Artificial intelligence allows computers to do things that were once only possible for humans. For example, computers have always been able to do calculations but with Artificial Intelligence technologies, they can learn and make conclusions on their own.
Artificial Intelligence Technology is now being introduced in more devices and platforms that allow users to make on-the-go decisions while travelling or working from home. The start of AI can be traced back to the 1970s when the concept of algorithms was created. It wasn’t until Big Data became more accessible that AI technologies were feasibly implemented.
Fast-forward to 2012, with an abundance of data at our fingertips, the Cloud era–and Artificial Intelligence technologies–began to take off. To get the most out of your AI investment, it’s important that you map out a strategy that outlines precisely what data will be needed and who will be responsible for it.
AI amplifies human ingenuity, and the development of these technologies has helped form conclusions as well. For example, movie-streaming websites suggest movies, TV shows, and documentaries that are similar to your taste. Other aspects like when you’re reading the content and what day it is are also taken into consideration, so you receive content that’s tailored to your schedule. These websites are getting “smarter” as their databases continue to expand. The term big data refers to the large amount of data that is processed for analysis.
Big Data is a term that describes a lot of data in different formats. Artificial Intelligence needs lots of data to be effective and Big Data is the preferred word because many organisations are collecting unprecedented amounts of information.
When you fill out forms or make decisions that are recorded by the computer, that information is potentially added to a Big Data set. This can occur via both IoT and internet-based transactions.
Bigger, more specific, and better-quality sample data will provide the AI with the ability to be smarter and sound more human. It’ll also help predict future decisions more accurately and reveal patterns and trends that might not have been apparent at first glance. If you feed your AI with small amounts of poor-quality data, you will ultimately harvest bad and biased results.
AI is often split into two parts, Machine Learning (ML) and Deep Learning (DL). ML can be thought of as the process where a system begins to take the information it’s learned and make logical decisions – which allows for quick, decisive turnarounds. DL can be used to make even more intelligent decisions based on unfamiliar data; it understands the parameters better than ML does.
ML empowers computers to learn from the data they’re given and make accurate predictions. With Artificial Intelligence, computers can process information and learn to make decisions. Machine Learning is just one type of AI and an important part in realising the power of AI.
Deep Learning is a type of Machine Learning and basically the next step in the evolution of ML. DL Algorithms are inspired by the information processing pattern that can be found in our brains. Humans use their brains to identify patterns and DL algorithms can be taught to do the same thing.
GDPR has a broad focus on data processing for personal data – especially large amounts of it. Its impact is widespread, and organisations of all sizes have been forced to adopt stricter guidelines.
There are different laws that come into play between AI and GDPR. While AI can help tackle GDPR violations, there are also parts of this regulation where companies of all sizes are turning to Big Data collecting and analytics. They use the input they get from Big Data to generate quantitative statements for GDPR compliance. However, the implementation and deployment of AI in the workplace have hit messy roadblocks in GDPR.
With a large amount of data Artificial Intelligence needs, it can be tricky to make sure your business follows GDPR regulations. AI can provide quick detection of data vulnerabilities, but there are still pressing issues regarding transparency and the right to explanation. It’s difficult for humans to understand the logic behind AI’s decisions.
Despite this, AI is currently the only viable solution to tackling data security issues. It provides a level of personalisation that can’t be achieved by other forms of technology. Nevertheless, it’s important to note that algorithms in Machine Learning are influenced by the data in their training sets and they won’t automatically comply with GDPR unless they are programmed explicitly to do so.
The Microsoft 365 platform already comes with AI-powered features integrated into all the apps your company is used to. These applications help employees have an even better work experience by amplifying their skills, promoting teamwork, and uncovering hidden insights. Microsoft 365 also offers protection against cyber-attacks and malware, making sensitive business and personal data safe.
Microsoft 365 can quickly and efficiently provide actionable insight on anything you’re looking for. Personalize your search to your business network with insightful results. One of the best features of Microsoft 365 is its boundary-less search, which means that it searches across your devices, contacts, and files.
Artificial Intelligence enables your employees to present more inclusively with live captions and subtitles in Microsoft PowerPoint and in the web version of Outlook, the new features give Microsoft 365 users meeting insights, suggested replies with a meeting, smart time suggestions, and suggested locations. Outlook will access the Microsoft Graph and recommend useful information for your next meeting. It will also sort historical information such as; files shared via email, files stored in SharePoint, etc.
Microsoft Dynamics 365 AI for Sales has Artificial Intelligence built-in to help your sales team create personalisation. The AIs can use vast sets of data to facilitate planning, guide problem solving, and synthesize insights that are not humanly possible on their own.
Despite recent advances, artificial intelligence is still in its early stages of development. It will continue to improve as new sources of data are made available.
Everyone’s using their phone more than ever, which has led to an exponential rise in the amount of digital data being created. But current data storage solutions are struggling to keep up with demand. Most data storage today is on magnetic or optical media, which poses problems when it comes to the availability of space. Optical disks are significantly more compact and are not as reliable as other types of media due to their reliance on fragile materials.
Microsoft is currently working with the University of Washington to develop Project Palix which allows binary code to be encoded and then synthesized as manufactured DNA storage. This new DNA data storage can store 1,000 times as much as tape storage and lasts 2.4x as long at just 10 degrees Celsius.
Do you want to find out how AI can help your business? Get in touch with one of our IT experts to find out more.