Total Articles: 19 from 7 sources
AWS News
1. AWS Weekly Roundup: Claude Sonnet 5 on AWS, Amazon WorkSpaces for AI agents, AWS service availability updates, and more (July 6, 2026)
Published: 2026-07-06 15:46
Summary:
A couple of editions ago I wrote about what I find so energizing about working with startups Last week I got a fresh dose of it: I spent a few days with the AWS Startups team, listening to stories of founders talking about the problems they’re actually solving One story that stayed with me came […]
2. Upgrade Amazon EKS clusters with confidence using Kubernetes version rollbacks
Published: 2026-07-01 17:20
Summary:
Learn how Kubernetes version rollbacks for Amazon EKS let you reverse cluster upgrades within seven days This new feature provides a safety net for upgrade failures—no cluster rebuilds required—turning Kubernetes version upgrades into a reversible, low-risk operation.
3. Accelerate your infrastructure deployments by up to 4x with AWS CloudFormation Express mode
Published: 2026-06-30 21:30
Summary:
AWS CloudFormation speeds up infrastructure deployment with Express mode, enabling AI agents and developers to receive deployment confirmation in seconds and iterate faster Available in all commercial Regions at no additional cost.
Dropbox Engineering
1. How we used DSPy to turn AI evaluations into better responses in Dash chat
Published: 2026-06-25 16:30
Summary:
We used DSPy to improve LLM judges and optimize our chat experience, creating an evaluation-driven feedback loop that produced better outputs.
2. How Dropbox uses MCP and Dash to close the design-to-code security gap
URL: https://dropbox.tech/security/dropbox-mcp-dash-design-code-security
Published: 2026-06-12 18:00
Summary:
Using an agentic AI system to surface threat models during code review and spot gaps between security requirements and implementation.
GitHub Blog
1. Better tools made Copilot code review worse. Here’s how we actually improved it.
Published: 2026-07-10 15:57
Summary:
How migrating Copilot code review to shared Unix-style code exploration tools reduced review cost by reshaping agent workflows around pull request evidence The post Better tools made Copilot code review worse Here’s how we actually improved it. appeared first on The GitHub Blog.
2. How GitHub gave every repository a durable owner
URL: https://github.blog/security/application-security/how-github-gave-every-repository-a-durable-owner/
Published: 2026-07-09 16:29
Summary:
GitHub had over 14,000 repositories Here’s how we gave every active repository a validated owner in under 45 days, archived the rest, and made ownership the foundation for everything that followed The post How GitHub gave every repository a durable owner appeared first on The GitHub Blog.
3. Automating cross-repo documentation with GitHub Agentic Workflows
Published: 2026-07-08 21:11
Summary:
Explore how the Aspire team turns merged product changes into SME-reviewed docs pull requests, closing the gap between release and documentation The post Automating cross-repo documentation with GitHub Agentic Workflows appeared first on The GitHub Blog.
Google Developers
1. How the community trained Gemma to “Think” with Tunix and TPUs
URL: https://developers.googleblog.com/how-the-community-trained-gemma-to-think-with-tunix-and-tpus/
Published: 2026-07-11 10:12
Summary:
The Google Tunix Hackathon on Kaggle challenged developers to transform small, non-reasoning base models into general reasoning engines using Kaggle TPUs and a limited compute budget The winning teams achieved this by implementing multi-stage post-training pipelines that combined Supervised Fine-Tuning (SFT) with advanced alignment techniques like GRPO and SimPO Ultimately, the competition democratized AI development by proving that highly capable, structured reasoning models can be successfully trained by the community using accessible, open-source resources.
2. Gemma 4 12B: The Developer Guide
URL: https://developers.googleblog.com/gemma-4-12b-the-developer-guide/
Published: 2026-07-11 10:12
Summary:
The newly released Gemma 4 12B is a dense, multimodal model designed for high-performance local AI execution on consumer devices By introducing a novel, encoder-free architecture, it bypasses traditional visual and audio encoders to feed multimodal data directly into the LLM backbone.
3. Bringing Gemma 4 12B to your Laptop: Unlocking Local, Agentic Workflows with Google AI Edge
Published: 2026-07-11 10:12
Summary:
Google DeepMind’s Gemma 4 12B model brings agentic, multimodal AI capabilities to everyday laptops with 16GB of RAM, enabling local data processing and visual insight generation Users can leverage this model on macOS through the Google AI Edge Gallery for dynamic Python code execution and visualization, as well as via Google AI Edge Eloquent for completely offline voice dictation and text editing Additionally, developer workflows are enhanced by the LiteRT-LM CLI’s new serve command, which creates an industry-compatible local endpoint to power fully-local AI tools and agents.
Meta Engineering
1. Meta’s AI Storage Blueprint at Scale
URL: https://engineering.fb.com/2026/07/01/data-infrastructure/metas-ai-storage-blueprint-at-scale/
Published: 2026-07-01 16:00
Summary:
During the past year or so, the time between new-frontier-model releases has gone down from months to weeks Reliable and fast access to storage is important to both the speed and computational cost of this AI innovation The post Meta’s AI Storage Blueprint at Scale appeared first on Engineering at Meta.
2. 10 Years of Meta’s Commitment to Python
URL: https://engineering.fb.com/2026/06/30/open-source/10-years-of-metas-commitment-to-python/
Published: 2026-06-30 16:00
Summary:
This year marks Meta’s 10th consecutive year as a sponsor of the Python Software Foundation (PSF), the charitable organization dedicated to advancing, supporting, and protecting the open-source Python programming language and the community that sustains it Python is one of the world’s most influential programming languages, and we use it across our engineering stack, from […] Read More The post 10 Years of Meta’s Commitment to Python appeared first on Engineering at Meta.
3. Privacy-Aware Infrastructure in the AI-Native Era: An Asset Classification Case Study
Published: 2026-06-25 22:30
Summary:
Privacy controls — systems that enforce retention, access, allowed-purpose, downstream-sharing, or anonymization policies — require a reliable understanding of data to function Before such a control can operate effectively, it must know exactly what it is looking at This can be complex, as demonstrated by a field simply named “age“: In one context, it […] Read More
Netflix TechBlog
1. GenPage: Towards End-to-End Generative Homepage Construction at Netflix
Published: 2026-06-29 13:01
Summary:
This sequence includes the full structured homepage layout, with multiple rows and the entities inside them, so the model can generate the page holistically rather than scoring each row or entity in isolation.Figure 2 At a high level, WBC turns generation into token-level value prediction: given the user context and the tokens generated so far, the model learns to estimate the value of generating each possible next row or entity token.This objective is easier to optimize than page-level RL WBC post-training loss as we progressively enrich the user context tokens
2. Toward More Controllable AI Video Editing: An Early Research Exploration at Netflix
Published: 2026-06-23 00:31
Summary:
We believe this work can help advance the field in a way that’s both meaningful and responsible:Vera: a layered video diffusion model Vera generates only what needs to change as separate edit layers while leaving the rest of the video untouched, preserving the identities, performances, and other details from the source footage exactly as filmed.VOID: a video inpainting model for video object and interaction deletion Specifically, the counterfactual videos are generated by re-simulating the exact scene from the original video, but with the target object(s) or human removed
3. How Netflix Simplified Batch Compute with Kueue
Published: 2026-06-22 21:35
Summary:
Reservations are not required to use CMB, so a tenant can run out of shared capacity entirely In addition, our learnings are being leveraged by other internal teams, including those building Kubernetes-native training infrastructure, to inform their job scheduling and queuing configurations.Fair Sharing and PreemptionWith Kueue, Preemption-based Fair Sharing allows Netflix Batch to maintain reservation semantics while lending resources to other tenants when those reservations are not in use For our customers, this means that tenants can use more idle capacity from reservations, submit more jobs without the risk of starvation, and have quicker turnaround times for business-critical workloads.An example preemption configuration on a ClusterQueue that we would be using is as follows:apiVersion: kueue.x-k8s.io/v1beta2kind: ClusterQueuemetadata: name: “team-a-cq”spec: preemption: reclaimWithinCohort: Any withinClusterQueue: LowerPriorityWith these features deployed, Compute has seen a significant increase in average resource utilization.AcknowledgementThis work would not have been possible without the great work of the entire Compute team at Netflix.How Netflix Simplified Batch Compute with Kueue was originally published in Netflix TechBlog on Medium, where people are continuing the conversation by highlighting and responding to this story.
Stripe Engineering
1. Four travel and hospitality trends from HITEC 2026
URL: https://stripe.com/blog/trends-from-hitec
Published: 2026-06-23 00:00
Summary:
More than 6,000 hospitality executives and operators gathered in San Antonio last week for the HITEC conference The big topic: whether the industry’s AI investment is actually working Across four days and over 50 meetings, four trends stood out.
2. What Link data tells us about AI spending
URL: https://stripe.com/blog/what-link-data-tells-us-about-ai-spending
Published: 2026-06-18 00:00
Summary:
We analyzed spending patterns across the 250 million customers paying with Link We found that Link customers are spending more on AI than they were three months prior, investing heavily in platforms that let them build with AI.
Generated on 2026-07-11 10:12:11