Transformative Insights: Exploring AWS re:Invent 2023’s ML and AI Updates

Piyush Jalan
5 min readDec 4, 2023


Amazon Web Services (AWS) offers a comprehensive suite of machine learning (ML) and artificial intelligence (AI) services that empower businesses to harness the transformative potential of data. These services are designed to cater to a diverse range of applications, providing scalable and customizable solutions to meet varying business needs. In this blog post, I will take you through AWS re:Invent 2023 ML and AI impactful updates:

Amazon SageMaker

· Amazon SageMaker Studio now provides a faster fully-managed notebooks in JupyterLab

· Amazon SageMaker Distribution is now available on Code Editor based on Code-OSS and JupyterLab

· Introduced Code Editor, based on Code-OSS (VS Code — Open Source), in Amazon SageMaker Studio

· SageMaker Studio introduced a suite of IDEs, including Code Editor based on Code-OSS Visual Studio Code Open Source, improved and faster JupyterLab, and RStudio.

· Introduced a new onboarding and administration experience that makes it easy to setup and manage Amazon SageMaker domains. The setup and onboarding flow on console has been redesigned from the ground up to provide a friendlier one click experience for individual users and a step-by-step guide for Enterprise ML Administrators (Admins).

· Amazon SageMaker Clarify now supports foundation model (FM) evaluations [in preview]

· SageMaker introduced improved SDK tooling and UX for model deployment

· Introduced smart sifting of data for Amazon SageMaker Model Training [in preview]

· Introduced Amazon SageMaker HyperPod, a purpose-built infrastructure for distributed training at scale

· Amazon SageMaker launches new inference capabilities to reduce costs and latency

· Amazon SageMaker Pipelines now provide a simplified developer experience for AI/ML workflows

· Leverage FMs for business analysis at scale with Amazon SageMaker Canvas -SageMaker Canvas expands these capabilities by making it easy for customers to adapt FMs to the patterns and nuances of a specific use case, enhancing its performance in terms of response quality, cost, and latency.

· Introduced API support for creating Amazon SageMaker Notebook jobs

· Amazon SageMaker Canvas now supports natural language instructions for data preparation

· Amazon SageMaker launches a new version of Large Model Inference DLC with TensorRT-LLM support

Amazon Bedrock

· Meta Llama 2, Cohere Command Light, and Amazon Titan FMs can now be fine-tuned in Amazon Bedrock

· Stable Diffusion XL 1.0 foundation model from Stability AI is now generally available in Amazon Bedrock

· Claude 2.1 foundation model from Anthropic is now generally available in Amazon Bedrock

· Llama 2 70B foundation model from Meta is now available in Amazon Bedrock

· Evaluate, compare, and select the best FMs in Amazon Bedrock (Preview) — Model Evaluation on Amazon Bedrock allows users to evaluate, compare, and select the best foundation models for their use case.

· Now generally available, fully managed Agents for Amazon Bedrock enables generative AI applications to execute multi-step tasks across company systems and data sources.

· Amazon Bedrock now supports batch inference

· Amazon Titan Text models — Express and Lite — now generally available in Amazon Bedrock

· Amazon Titan Multimodal Embeddings foundation model now generally available in Amazon Bedrock

· Amazon Titan Image Generator foundation model in Amazon Bedrock now available [in preview]

· Safeguard generative AI applications with Guardrails for Amazon Bedrock (Preview)

· Knowledge Bases for Amazon Bedrock is now generally available

· New Discover Apps page for PartyRock, an Amazon Bedrock Playground — PartyRock has introduced a new Discover page, where top community-created apps will be curated by AWS.

· AWS Step Functions launches optimized integration for Amazon Bedrock

· Continued pre-training in Amazon Bedrock now available [in preview] — Continued pre-training in Amazon Bedrock is a new capability that allows users to train Amazon Titan Text Express and Amazon Titan Text Lite FMs and customize them using their own unlabeled data, in a secure and managed environment.

Gen AI

· Introduced new AWS AI Service Cards — to advance responsible AI — Introduced new AWS AI Service Cards, a resource to increase transparency and help customers better understand AWS AI services, including how to use them in a responsible way.

· Descriptive Bot Builder with Generative AI — Amazon Lex’s new Descriptive Bot Builder uses foundation models (FMs) from Amazon Bedrock to quickly create a fully functional bot in minutes.

· Assisted Slot Resolution with Generative AI — The Assisted Slot Resolution feature uses the advanced reasoning capabilities of FMs to improve accuracy and ultimately a better customer experience.

· AWS HealthScribe is now generally available — AWS introduced the general availability of AWS HealthScribe, a HIPAA eligible, generative AI-powered service designed to help healthcare application builders automatically create preliminary clinical documentation from patient-clinician conversations.

· Amazon Personalize now creates themes for recommendations using generative AI

Amazon Q

· AWS introduced Amazon Q (Preview) — With Amazon Q, employees can ask questions and get answers from knowledge spread across disparate content repositories, summarize lengthy reports, write articles, take actions, and much more — all within their company’s connected content repositories.

· Amazon Q in QuickSight simplifies data exploration with Generative BI capabilities (Preview) — Amazon QuickSight introduced three new natural language capabilities enabled by Amazon Q for business users. Launching in preview, these capabilities can summarize dashboards, generate mini dashboards to answer data questions, and build stories explaining data.

· Amazon Q in Connect now offers generative AI powered agent assistance in real-time

· Introduced Amazon Q expert capabilities for AWS (Preview)

Amazon Lex

· Introduced utterance generation for Amazon Lex — Amazon Lex’s machine learning model uses utterances to recognize and respond to the user intent.

· Introduced Conversational FAQ with generative AI for Amazon Lex (Preview) — a preview of the QnAIntent in Amazon Lex.

Amazon Transcribe

· Powered by foundation model, Amazon Transcribe now supports over 100 languages

· Amazon Transcribe Call Analytics now offers generative call summarization (preview)

Amazon CodeWhisperer

· Introduced new enhancements to Amazon CodeWhisperer — AWS introduced new updates to Amazon CodeWhisperer, including support for Infrastructure as Code (IaC), AI-powered code remediation, and expanded language support for security scanning, all generally available.


· Amazon Monitron launches Ex-rated sensors for hazardous locations -Amazon Monitron is an end-to-end system that uses machine learning to detect abnormal conditions in industrial equipment to enable predictive maintenance.

· Amazon Personalize has introduced the new Next-Best-Action recipe to help users recommend actions that their users have a high probability to take in real-time.

· AWS introduced CloudWatch Logs Anomaly Detection and Pattern analysis — AWS announces the general availability of a suite of machine-learning powered log analytics capabilities in CloudWatch, including automated log pattern analysis and anomaly detection. Using these new capabilities, users will be able to easily interpret their logs, identify unusual events, and use these insights to steer and accelerate their investigation.

Please feel free to write @ for any queries on AWS ML and AI updates & stay tuned for next write-up.

Thank you!



Piyush Jalan

Cloud Architect | Cloud Enthusiast | Helping Customers in Adopting Cloud Technology