Posts for Tag: Amazon

Amazon AWS Re:Invent 2023 Ushers in a New Era for AWS

AWS recently held its annual re:Invent conference, showcasing exciting new offerings that demonstrate the company's continued leadership in cloud computing and artificial intelligence. This year's event had a strong focus on how AWS is pioneering innovations in generative AI to provide real business value to customers.

CEO Adam Selipsky and VP of Data and AI Swami Sivasubramanian headlined the event, announcing breakthrough capabilities spanning hardware, software, and services that mark an inflection point for leveraging AI. AWS is committed to progressing generative AI from leading-edge technology into an essential driver of productivity and insight across industries.

Highlights from Major Announcements

Here are some of the most notable announcements that give a glimpse into the cutting-edge of what AWS is building:

  • Amazon Q - A new AI-powered assistant designed for workplace collaboration that can generate content and code to boost team productivity.  
  • AWS Graviton4 and Trainium2 Chips – The latest generation AWS processor and accelerator chips engineered to enable heavy AI workloads like training and inference.  
  • Amazon Bedrock Expansion – New options to deploy and run custom models and automate AI workflows to simplify integration.
  • Amazon SageMaker Updates – Enhanced capabilities for novices and experts alike to build, train, tune and run machine learning models faster. 
  • Amazon Connect + Amazon Q - Combining AI assistance and customer service software to help agents respond to customers more effectively.

AWS underscored its commitment towards an intelligent future with previews showcasing bleeding edge innovation. This vision crystallizes how human-AI collaboration can transform customer experiences and business outcomes when generative AI becomes an integral part of solution stacks. Re:Invent 2023 ushered in this emerging era.

As the curtain falls on AWS re:Invent 2023, the message is clear: AWS is not just keeping up with the pace of technological evolution; it is setting it. Each announcement and innovation revealed at the event is a testament to AWS's unwavering commitment to shaping a future where technology is not just a tool but a catalyst for unimaginable growth and progress. The journey of AWS re:Invent 2023 is not just about celebrating achievements; it's about envisioning and building a future that's brighter, faster, and more connected than ever before.

Amazon Bets $4 Billion on the Consumer LLM Race

With the rise of new Large Language Models (LLMs), especially in artificial intelligence (AI) and machine learning, the race to the top has never been more intense. The big tech giants - Google, Microsoft, and now Amazon - are at the forefront, controlling significant portions of the consumer LLM markets with heavy investments.

A recent headline reveals Amazon's latest investment strategy, shedding light on its ambitious plans. Amazon has agreed to invest up to $4 billion in the AI startup Anthropic. This strategic move highlights Amazon's growing interest in AI and its intention to compete head-to-head against other tech behemoths like Microsoft, Meta, Google, and Nvidia.

This substantial investment comes with the initial promise of $1.25 billion for a minority stake in Anthropic. This firm operates an AI-powered text-analyzing chatbot, similar to Google's Bard and Microsoft-backed OpenAI. With an option to increase its investment up to the entire $4 billion, Amazon's commitment to AI and the future of technology is evident.

Furthermore, reports earlier this year revealed that Anthropic, already having Google as an investor, aims to raise as much as $5 billion over the next two years. This ambition signals the high stakes and intense competition in the AI industry.

Google and Microsoft's Dominance

While Amazon's recent entry into heavy AI investments is making headlines, Google and Microsoft have long been dominant players in the AI and LLM markets. Google's vast array of services, from search to cloud computing, is powered by their cutting-edge AI technologies. Their investments in startups, research, and development have solidified their position as leaders in the field.

On the other hand, Microsoft has been leveraging its cloud computing services, Azure, combined with its AI capabilities to offer unparalleled solutions to consumers and businesses alike. Their partnership with OpenAI and investments in various AI startups reveal their vision for a future driven by artificial intelligence.

The Open Source Alternative Push by Meta

In the face of the dominance exerted by tech giants like Google, Microsoft, and Amazon, other industry players opt for alternative strategies to make their mark. One such intriguing initiative is Meta, formerly known as Facebook. As the tech landscape becomes increasingly competitive, Meta is pushing the boundaries by championing the cause of open-source technologies.

Meta's open-source foray into LLM (Large Language Models) is evident in its dedication to the Llama platform. While most prominent tech companies tightly guard their AI technologies and models, considering them as proprietary assets, Meta's approach is refreshingly different and potentially disruptive.

Llama Platform: A Beacon of Open Source

As a platform, Llama is engineered to be at the forefront of open-source LLM models. By making advanced language models accessible to a broader audience, Meta aims to democratize AI and foster a collaborative environment where developers, researchers, and businesses can freely access, modify, and contribute to the technology.

This approach is not just philanthropic; it's strategic. Open-sourcing via Llama allows Meta to tap into the collective intelligence of the global developer and research community. Instead of relying solely on in-house talent, the company can benefit from the innovations and improvements contributed by external experts.

Implications for the AI Ecosystem

Meta's decision to open-source LLM models through Llama has several implications:

  1. Innovation at Scale: With more minds working on the technology, innovation can accelerate dramatically. Challenges can be tackled collectively, leading to faster and more efficient solutions.
  2. Leveling the Playing Field: By making state-of-the-art LLM models available to everyone, smaller companies, startups, and independent developers can access tools once the exclusive domain of tech giants.
  3. Setting New Standards: As more organizations embrace the open-source models provided by Llama, it might set a new industry standard, pushing other companies to follow suit.

While the open-source initiative by Meta is commendable, it comes with challenges. Ensuring the quality of contributions, maintaining the security and integrity of the models, and managing the vast influx of modifications and updates from the global community are some of the hurdles that lie ahead.

However, if executed correctly, Meta's Llama platform could be a game-changer, ushering in a new era of collaboration, transparency, and shared progress in AI and LLM.

The Road Ahead

As big tech giants continue to pour substantial investments into AI and dominate vast swathes of the consumer LLM markets, consumers find themselves at a crossroads of potential benefits and pitfalls.

On the brighter side, the open-source movement, championed by platforms like Meta's Llama, offers hope. Open-source initiatives democratize access to cutting-edge technologies, allowing a broader spectrum of developers, startups, and businesses to innovate and create. For consumers, this means a richer ecosystem of applications, services, and products that harness the power of advanced AI. Consumers can expect faster innovations, tailored experiences, and groundbreaking solutions as more minds collaboratively contribute to and refine these models.

However, the shadow of monopolistic tendencies still looms large. Even in an open-source paradigm, the influence and resources of tech behemoths can overshadow smaller players, leading to an uneven playing field. While the open-source approach promotes collaboration and shared progress, ensuring that it doesn't become another arena where a few corporations dictate the rules is crucial. For consumers, this means being vigilant and supporting a diverse range of platforms and services, ensuring that competition remains alive and innovation continues to thrive.

New Feature: Amazon Review Feed is Now Live

We are super excited to announce the availability of the Amazon Review feed as a source for your prompt apps. Now you can create prompt apps to access Amazon reviews for any product on Amazon! Yep, it is now live.

How does it Work?

First, you can log on to your account by clicking the Sign In link in the main menu.

Once logged in, click on the New Prompt App menu option from your menu, which can be accessed by clicking on your profile image.

Once you are in the new prompt app editor, you can enter your prompt text that needs to be added to the Amazon feed. Once you are ready to connect the Amazon feed, look for a new button called the Amazon, as shown below:

This will open a dialog box, as shown in the figure below:

You can add an Amazon product link from or leave this blank. Remember, if you paste a URL in the popup window, the prompt app will only use that URL for all runs. So, it is best to leave the URL empty so users can paste their Amazon product link. Now click on the Apply button. It will insert the following tag in the current prompt app. 

Make your other choices related to making the prompt app available -- free, paid or private. Then, publish the app. Once published, you can test-run it by clicking on the Run button. Here is an example of an Amazon feed enable app that we are running:

Go to and select a product you want to use for the test. Then, copy the product URL from the website and paste it in the prompt app's dialog window.

Typically, Amazon product links are very long. Here is an example one:

When you paste it in the run dialog, it will automatically shorten it to the following format:<ASIN>

For example, the one shown above as a sample, it will look like:

As soon as we detect that you have pasted an Amazon link, it will convert to the above format and also show two different options as shown in the figures below:

This option lets users choose to apply for the most recent or top reviews. This becomes important for the next option:

You can choose how many reviews you wish to apply to this prompt. The previous filter -- Top Reviews or Recent Reviews -- decides which reviews are fetched in what order. 

Once you choose more than ten reviews, the system will automatically disable live run (red run button) and only allow you to schedule run using the blue (turtle) run mode. Since fetching many reviews takes time, we only offer running large review jobs in the background.

Once you have made the choices, you can choose a run button (red or blue) and wait for the system to let you know when it is done. 

If you are scheduling a large review run, the job will be queued in the background, which you can check from your menu option: BACKGROUND TASKS.  This shows all the background tasks that are queued and all the past ones that ran already.

Here is how the list of background tasks shows:

You can view pending or completed tasks. You can view the results using the View Results button for completed tasks. You can also cancel any pending task using the Cancel button.  When you view results, it brings you to the prompt app page where the results are shown in the Run History section as shown below:

You can view the response of the prompt app as text or PDF document. Also, you can download the anonymized review data used for the prompt run as a CSV file. The product information is also available as a JSON data file,

Can I Compare Multiple Products?

Currently, we limit one Amazon feed per prompt app. We are working on an advanced version of CPROMPT that will allow users to use multiple Amazon feeds to analyze multiple products. This special edition of CPROMPT will serve as a functional demonstration of the advanced apps that you can create in the future. CPROMPT app creation tools are limited in Beta and only allow you to create single-feed apps.

Why Does it Cost So Much?

We have multiple API and compute costs associated with Amazon product review feed data pipeline. At lower volume, we pay higher price. Once we have a higher volume, we will be able to lower the price of the data analysis.