AWS Innovate in a Flash(AI/ML)
In the day in age we are in today, there have been incredible strides taken in the sectors of Artificial Intelligence(AI)/Machine Learning(ML). Some of the most famous technologies include self-driving cars and bio-metric technologies and continue to expand in many sectors of the market. However, behind each of these, there are specific technologies that allow for the computer to make smart decisions. AWS has invented and introduced various new pieces of technologies that can tackle strenuous tasks using AI and ML.
Recently attending the AWS Innovate AI/ML Conference, I was able to gain a grasp on the numerous features AWS uses for their robots and computer-made-decisions. For a little background, Amazon utilizes robots in there warehouses to keep everything organized and increase efficiency for the users and the consumers. As you can see, the robots bring racks of shelves with items, each organized in compartments to the worker, ready to move on to the next stage. In addition, the AmazonGo store uses high-end and futuristic lenses and software, emphasizing their “no-cashier” service. In essence, a consumer picks-up what they want and the camera detects it and puts in in the cart of the individual.
In this blog, I will go over a brief yet high-end overview of the products used in the conference and their applications in use-cases and real life. Let’s get right into it!
Amazon SageMaker
One of the highlights of the conference was Amazon SageMaker, an intellectual piece of software excellent for Data Scientists and other data related operations. In essence, Amazon SageMaker is a tool that utilizes data provided by the user and deploys various different models on its own. In the end, the user can choose the best model for their use-case and use that in any operations that they need in the future.
Breaking this down deeper, I will provide an easy, yet sophisticated example to explain the brilliance in the software. In this example, I will use real estate, which include the variables: # of bathrooms, # of bedroom, and location, each of which are a dependent variable when calculating the price of the property. With the data that I have on a sample of houses in Texas, I would place data in a S3 Bucket in a csv file . Also, using Jupyter Notebooks, I will type up my scripts in Python with the numerous functions and databases I would like to use for this specific process(There are many example sets AWS provides if you would like to use one). After, I would use Amazon SageMaker to create various different models. Once I choose the model I would like to use, I would able to have a graphical interface to analyze, along with more information in regards to the model.
Amazon SageMaker also has an autopilot mode, where all of this done in a touch of a button. In this case, the computer makes the right judgement calls and based on these calls, the user will get an analysis of the model quicker and throughout the entire process, the user will always have control of the operation. In seconds, you will all the information needed in regards to your data and a model that can stretch miles for the company and the consumer, along with the scripts used, which are editable if need be.
Amazon Kendra
We’ve all been there. Scrolling through Google trying to find the right information for our project and yet, nothing can be found. When it comes to searching on Google or Firefox, the computer uses a very basic algorithm to decipher the websites that relate to your search, but is not what you are exactly looking for. There are still websites present taking up your space and time. To solve this, Amazon has introduced Kendra to their AI/ML products!
In essence, Amazon Kendra is a search engine that uses AI/ML to find the write website for your needs. When you search on this platform, the computer scans the phrase and uses reading-comprehension and context to display the websites that most closely match your search. Now using AI/ML in a simplistic manner will make retrieving data much easier and smoother for employees and the consumers.
Amazon CodeGuru
In society today, developers and software engineers are bombarded with bugs coming about in their software. These bugs are not only costly for the developer and company but are also inefficient for consumers who use the software. A catastrophe in the eyes of many engineers…
Amazon has decided to re-invent and solve such issues with the help of AI/ML technologies. Amazon CodeGuru detects the most important and expensive bugs in the program and provides an effective solution to the problem. No matter how many scripts a developer has, CodeGuru will inspect each on and will provide feedback and suggestions on the bugs or even, making the code much more efficient. Think of it as GPT-3 but on steroids…
Personally, I am an avid coder so, this AI solution was something that I felt needs to be used on a daily basis. No one is a perfect coder and with Amazon CodeGuru, the art of coding get much more interesting. No more tugging at your hair to solve a bug, hand it over to Amazon instead.
AWS Panorama
Many individuals may have not heard of the AWS Panorama. In general, AWS Panorama is a piece of hardware created by AWS and this hardware uses Machine Learning and aims to do computer vision projects for the user. The devices connect to cameras and lenses and from there, will be able to do all sorts of projects. The main targeted use-cases for this technology are to inspect manufacturing lines in warehouses/factories and analyze traffic in retail stores.
A prime example of AWS Panorama today is in the AmazonGo store. For those who do not know, AmazonGo is Amazon’s take on the future of retail. There is no cashier, the user picks up whatever they want, leaves, and the total price of the object will be deducted from their Amazon account. In this store, Amazon utilizes Panorama to detect the bar-codes of each item and attaches that item to the user and their account. If the user puts an item back, the computer will know and delete the item from your “virtual” cart. In addition, Panorama tracks the foot pattern that the user takes and provides the data to the user once they leave the retail store. This is nice as the owner of the store can analyze the patterns to which aisles customers go and as causation, put products that are not that popular over there, as there is a larger cluster of customers present.
The applications of AWS Panorama are endless. There is so much that can be done with the device, besides the typical use-cases provided by Amazon. To get your hands on the device, use this link and begin your experimentation process!
In Conclusion…
Although Amazon Innovate AI/ML may have not been re:Invent, I was able to learn and understand many of the new technologies introduced by AWS. From SageMaker to Panorama, AWS has utilizes various aspect of Artificial Intelligence and have created products that will revolutionize the tech-world. Soon, we will live in a society where each one of these products will be controlling computers, robots, and other devices to do task unimaginable. The only left for us to do is Wait…
