IMPROVE MACHINE LEARNING DEPLOYMENT WITH NEW RE:INVENT 2020 AWS LAMBDA FEATURE

AWS Lambda was released back in 2014, becoming a game-changing technology. By adopting Lambda, many developers have found a new way to build micro-services that could be easily achieved. It comes with many additional advantages such as event-based programming, cloud-native deployment, and the development of the now well-known infrastructure-as-code paradigm.

A paradigm-shifting technology like AWS Lambda had to define its own standards to support all the modern app development lifecycle requirements. To make things easy to develop, Lambda decided to offer the easiest way of code project management: the zip file format.

Then, packaging and deploying a code function to…

RE:INVENT 2020 SESSIONS PICKS FOR DEVELOPERS AND MACHINE LEARNING PRACTITIONERS

This year will be remembered for many reasons. It has been a year of big changes in our lives and habits and a time when we found new ways to do the things we love. 2020 will be remembered as the first year without Amazonians from everywhere gathering in Vegas for the traditional re Invent.

Luckily, it won’t be a year without re:Invent because AWS decided to shift the conference completely online, with a catalog of almost 2000 unique sessions ranging from IoT to machine learning applications to infrastructure and serverless.

As a developer and a machine learning practitioner, digging…

CAN YOU OBTAIN THE SAME ACCURACY OF A CUSTOM TRAINED ML MODEL WITH AMAZON REKOGNITION CUSTOM LABELS?

ML classification: Amazon Rekognition or Amazon SageMaker?

Computer vision problems have been tackled using neural networks in recent years, obtaining unprecedented results and continuously raising the bar of accuracy to near-human performances.
In this article, the focus is set on image classification in an uncommon context related to a Neosperience customer that provided the opportunity to compare two different approaches: Amazon Rekognition Custom Labels and Amazon SageMaker custom model.
Both approaches have advantages and could find their spot in a given context, but Amazon Rekognition Custom Labels offer an interesting tradeoff between time-to-market and cost.

Alisea

Machine Learning applications are steadily shifting from research domains to industry, opening…

DEMOCRATIZING AI FOR EVERY DATA SCIENTIST, WITH MODERN TOOLS

In real-world applications, managed AI services such as Amazon Rekognition and Amazon Comprehend offer a viable alternative to dedicated data science teams building models from scratch. Even when a use case requires model re-training with purpose-built datasets such as custom image labels or text entities, it can be easily achieved with Amazon Rekognition Custom Labels or Amazon Comprehend Custom Entities.

These services offer state of the art machine learning model implementations, covering several use cases. Such models are not a feasible approach in some contexts. It could happen either because the underlying network requires being deeply customized to data scientists…

Some of the companies joining us in the last few months brought non only strong domain expertise and technical competencies in their field (i.e., MIkamai, LinkMe) but also widely adopted products, like Workup RubinRed Digital Commerce platform. Many to come in the next months as soon as we find top performers in their fields, willing to scale up and join our family. On a product strategy basis, it has not been easy to think which evolution model was the best to provide the best value for our customers. On one side, we could adopt a centralized model with firm product…

Since we started scaling up Neosperience from a single company to a group, while onboarding people with different stories and experiences, making everyone feel comfortable has been one of our top priorities. We know this posed several challenges we had to consider to reach the ambitious goal of having everyone “feel like being at home” within Neosperience. We know that the three keys driving people’s motivation are autonomy, mastery, and purpose. Such principles are good at keeping a single person engaged with a company or a team. Unfortunately, they do not provide sufficient enough guidelines about the strategies to help…

On June, 16th Amazon Web Services released the long-awaited feature of AWS Elastic File System (EFS) support for their AWS Lambda service. It is a huge leap forward in serverless computing, enabling a whole set of new use cases, and could have a massive impact on our AI infrastructure, thus reducing machine learning inference costs down to pennies for a wide number of applications.

The most exciting feature of Elastic File System is its capability to be mounted both on EC2 virtual machines, Fargate containers, and AWS Lambda. This feature is not anything new on the EFS domain. It has…

Il mondo IT non è esente dal fascino delle “mode del momento”: soluzioni che magari sono state adottate da aziende considerate punti di riferimento e che assumono nell’immaginario collettivo il ruolo di “no brainer” diventando il nuovo status quo, almeno per alcuni mesi, in attesa che la nuova “moda” prenda il posto della precedente. Il più delle volte si tratta di soluzioni che hanno più di un razionale forte nella loro adozione da parte delle aziende che le hanno proposte per prime. …