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AWS re:Invent 2024: A Look at the Innovations Shaping the Future

admin — Thu, 19 Dec 2024 14:49:28 +0000

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AWS:reInvent 2024: A Look at the Innovations Shaping the Future

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AWS:reInvent 2024

AWS re:Invent 2024: A Look at the Innovations Shaping the Future

AWS has done it again. At its annual re:Invent 2024 event, Amazon Web Services announced a series of updates and releases that transform the way businesses and organizations of all sizes operate in the cloud. From generative AI enhancements to new security and infrastructure capabilities, here’s the most relevant to staying ahead of the curve.

At ITERA, we were privileged to be present to explore these innovations first-hand and bring you the tools and solutions your business needs to stay competitive.

1. Generative artificial intelligence and machine learning

Generative AI was the main focus at re:Invent 2024. AWS introduced a number of new features to take automation and analytics to a new level:

Amazon Nova Models: A suite of AI models that includes:
– Nova Canvas: Professional image generation.
– Nova Reel: Creation of high-quality videos.
– Nova Understanding Models: Text and vision capability in more than 200 languages.
Amazon Bedrock Intelligent Prompt Routing where you’ll get:
– Intelligent Fast Routing: Optimize costs and latency in generative AI applications.
– Bedrock Agents: Collaboration between agents and automatic reasoning check for greater accuracy and fewer “hallucinations”.
Amazon Q Developer: New capabilities for automated code reviews and operational improvements.
Amazon Bedrock Marketplace: You’ll Access Over 100 Base Models in One Place

These tools simplify development, optimize performance, and improve the quality of AI-powered work.

2. Customer experience and business solutions

AWS has also strengthened its services to improve customer experience and streamline workflows:

Amazon Connect: Integration with WhatsApp Business and secure data collection features powered by generative AI.
Salesforce Contact Center with Amazon Connect (SCC-AC): An AI-based contact center integrated with CRM to maximize ROI.
Amazon QuickSight: Amazon Q-powered scenario analytics that improve business intelligence and decision-making.
Queryable object metadata for Amazon S3 buckets: Improves the ability to efficiently search and filter information within a bucket.

These solutions make it easy to personalize and automate customer interactions.

3. Data and analytics: All in one place

For those looking to take data analytics to the next level, AWS announced:

Amazon SageMaker Unified Studio: A unified platform for data, analytics, and artificial intelligence, simplifying information management.
Amazon SageMaker Lakehouse: ETL-free integrations with popular applications and databases for faster analysis.
Amazon S3 Innovations:
– S3 tables: Optimizes query performance.
– S3 Metadata: More Efficient Data Discovery

These updates facilitate the access and analysis of large volumes of information, streamlining processes.

4. Security and infrastructure: Robust innovations

Security and infrastructure remain top priorities for AWS, with enhancements that make it easier to migrate and protect data:

Amazon EVS: The fastest solution for migrating VMware workloads on AWS.
Amazon EKS Auto Mode: Automation in Kubernetes cluster management.
Amazon DynamoDB Global Tables: Now with multi-region consistency for highly available applications.
AWS PrivateLink: Enhanced private and secure connectivity options.

5. Strategic collaborations and alliances

AWS also announced enhancements to its collaboration with SAP:

Grow with SAP on AWS: Available in AWS Marketplace for faster adoption of cloud ERP.
RISE Migration Support Service with SAP: Makes it easy to transition workloads to AWS.
Amazon Nova Integration: Empowering SAP with generative AI capabilities.

The cloud of the future is here

AWS re:Invent 2024 undoubtedly reaffirms Amazon Web Services’ commitment to offering more advanced, efficient, and secure solutions. The announced innovations not only accelerate the adoption of cloud technology, but also boost productivity, reduce costs, and open up new business opportunities.

At ITERA, we are ready to help you implement these new features and take your company to the next level.

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La entrada AWS re:Invent 2024: A Look at the Innovations Shaping the Future se publicó primero en Itera Process.

Amazon Web Services Generative AI

admin — Thu, 05 Sep 2024 02:56:48 +0000

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Amazon Web Services Generative AI: Is it safe to deploy Generative AI with AWS?

Let’s talk about security and Generative AI. What happens to security when we use generative artificial intelligence? This is a question that is constantly repeated in conversations with customers, especially when thinking about developing solutions with confidential information of companies, such as customer financial data, personal information or processes, for example.

Generative AI, such as ChatGPT, is partly responsible for this questioning. Those who have used it know that its benefits are achieved thanks to its nature: learning from open data and from the data of the users who use it daily.

This feature can be insecure, and as such, no company should build or share classified information with tools that don’t guarantee the privacy and security of their data.

Amazon Web Services Generative AI:

The AWS Cloud offers Generative AI services that enable users to securely develop solutions with diverse use cases, with a focus on protecting customer data. To answer the initial question, it’s important to understand the AWS security background.

What is Amazon Bedrock?

It is AWS’s core Generative AI service. Amazon Bedrock is a fully managed service that offers several foundational generative AI models built by different vendors, with a set of capabilities to build fully customizable AI applications privately and securely. This service allows us to develop intelligent solutions that respond according to the needs, data and settings of each company.

In addition, this product applies the shared responsibility model, in which AWS is responsible for protecting the infrastructure where applications run, while users are responsible for configuring security and related services.

It is important to note that:

Amazon Bedrock does not store or log requests or results.
Amazon Bedrock does not use user-provided instructions for training models or distribute them to third parties.

How does Generative AI work on AWS?

On AWS, generative AI models are provided by different vendors through a deployment account in each region, managed by the Amazon Bedrock team.

Providers do not have access to AWS accounts; the Amazon Bedrock team makes a copy of the inference and training software. As a result, suppliers do not have access to records or any customer information.

In short, the copy of the Generative AI model used only contains the trained software, not including the information with which it was trained. No additional information is generated for training by providers, as they do not have access to data or any other information outside of AWS.

When a generative AI solution is enabled with this service, one individual copy is generated in each AWS account, as well as one copy per region. This means that data is not stored in a common place; each customer has their own copy of Amazon Bedrock models.

In addition, AWS Generative AI encrypts information from sessions using an AWS-managed key, and all requests to the models’ API are made over a secure SSL connection.

You can even use AWS PrivateLink to create a private connection between your own VPC and Amazon Bedrock, without using an Internet access port.

Best Practices: Key Principle for Generative AI in your Company

Like any other Amazon Web Services service, you need to build an infrastructure with good security practices, such as:

Access control with MFA and the principle of least privilege.
Create a separate VPC with a subnet environment and port access control.
Adding services such as Security Hub and GuardDuty.
Monitoring with Amazon CloudWatch and Amazon EventBridge.

In other words, an environment must be built under the best practices of the Amazon Web Services security pillar, since everything that is developed must comply with these guidelines, regardless of whether the Generative AI models are built and deployed safely.

Therefore, with the help of a specialized partner, a solution can be built in a highly secure environment.

Facts about Security and Generative AI:

Only 24% of Generative AI projects are being secured due to executives not prioritizing security.
A new and challenging landscape requires companies to build foundations of governance, secure application development, data governance, and usage models.
90% of the Generative AI requirements are considering specialized tools and partners.
Currently, the main risk of Generative AI lies in open source services and the indiscriminate use by collaborators of these tools, who upload information from companies without considering the operating logic.

All this in contrast to cases that are built with a service that must comply with regulations and standards, as is the case with Amazon Web Services.

See you in the Cloud!

As an AWS Advanced Partner and strategic business partner, we help organizations on their path to the future of cloud and generative AI. With a proven track record of success in cutting-edge technology implementations and through the expertise of our team of certified specialists, we facilitate enterprise digital transformation.

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La entrada Amazon Web Services Generative AI se publicó primero en Itera Process.

Generative AI

admin — Tue, 23 Apr 2024 19:39:53 +0000

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HOW TO APPLY GENERATIVE AI IN BUSINESS

Since 2023, Generative AI has become a global trend due to its incredible ability to produce intelligent responses. In organizations, questions arise about how to start applying it, where to focus it and what is required to integrate it into current processes.

Generative AI is not aimed at displacing jobs, as is often thought, but is aimed at increasing the productivity of staff and each area of the business, shortening implementation times and supporting content design.

What is Generative AI?

It is a type of artificial intelligence capable of creating a wide variety of data and content such as images, videos, texts, conversations and even executing tasks and code through a natural, more human language. It represents the next step in the evolution of artificial intelligence, which can be trained to understand any complex topic.

How to apply Generative AI?

The first step in applying Generative AI in a business is to understand its scope and how it works, as it is essential to identify areas of opportunity within the various departments of the organization.

Depending on the line of business, Generative AI can be used in various ways, even beyond content generation. Here are some examples:

Marketing and sales:

Gen AI models can help generate:

– Content development, such as blog articles, social media posts, web content, and brochures.

– Assertive messages for email campaigns, LinkedIn messages and product sheets.

– Personalized marketing that analyzes data to develop content adapted to the customer’s tastes, preferences, and regional trends, thus generating greater engagement.

Innovation:

Generative AI can offer innovative possibilities for the business, such as the generation of proposals for new prototypes and products based on the company’s activity, thus facilitating the rapid iteration and evolution of the work team, without the need for complex human analysis.

Virtual Assistants and Chatbots:

Although these already exist, Generative AI elevates the experience to another level. They can now better understand human language and respond independently to customer needs, offering support, answering questions, and conducting sales transactions closer to interacting with human staff.

Automation of repetitive tasks:

Generative AI can take care of tasks such as data capture, reporting, and inventory management, freeing up time for the team to focus on strategic tasks. It can also be applied in financial analysis to reduce costs in areas such as logistics, marketing, sales and production, as well as in extracting useful information from large volumes of data.

Fraud detection and security:

Gen AI models can analyze data patterns to detect anomalies and potential security breaches, safeguarding information and preventing fraud. They can also identify unusual spending patterns or accesses that may indicate fraudulent activity.

Generative AI ideas according to the line of business:

Financial companies:

Gen AI can generate customized investment plans for each client, based on their income, expenses, and investment goals. It can also assist in fraud detection and investment risk analysis, looking for profitable opportunities in the stock market.

Retail Companies:

For these companies, Generative AI can facilitate the development of prototypes and new products, as well as offer personalized experiences to customers, allowing them to personalize products and offering them purchase recommendations based on their consumption history and preferences.

In short, Generative AI offers a wide range of possibilities to improve efficiency and innovation in business. In another article, we’ll explore Amazon Web Services (AWS) solutions focused on Generative AI to show how they can be applied in your organization.

Implement Generative AI solutions in your company

At Itera, we accompany our clients from the adoption to the implementation of this technology. We carry out explanatory sessions to understand how it works and generate creative ideas for its use. In addition, we offer demos and proofs of concept to verify the viability of the initiative, and we provide support for work teams to adopt Generative AI in a positive way.

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La entrada Generative AI se publicó primero en Itera Process.