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    <title>InfoQ</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ feed</description>
    <item>
      <title>AI Is Moving up the Software Lifecycle: From Code Review to PRD Governance</title>
      <link>https://www.infoq.com/news/2026/06/ai-prd-code-review-governance/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;Technology companies are extending AI beyond code generation into earlier stages of the software lifecycle, including PRD validation, design inputs, and code review. Initiatives from Uber, DoorDash, and Cloudflare highlight a shift toward AI-driven governance layers that evaluate engineering artifacts before implementation while preserving human oversight across the development pipeline.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Software Engineering</category>
      <category>Productivity</category>
      <category>AI Architecture</category>
      <category>Governance</category>
      <category>AI Assisted Coding</category>
      <category>Code Reviews</category>
      <category>Workflow / BPM</category>
      <category>Requirements</category>
      <category>AI Development</category>
      <category>Software Development Lifecycle</category>
      <category>Documentation</category>
      <category>Agents</category>
      <category>AI Coding</category>
      <category>Architecture &amp; Design</category>
      <category>Culture &amp; Methods</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Wed, 24 Jun 2026 14:57:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/ai-prd-code-review-governance/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-06-24T14:57:00Z</dc:date>
      <dc:identifier>/news/2026/06/ai-prd-code-review-governance/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Rules for Understanding Language Models</title>
      <link>https://www.infoq.com/presentations/5-principles-llm-behavior/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/presentations/5-principles-llm-behavior/en/mediumimage/naomi-saphra-medium-1781688751052.jpg"/&gt;&lt;p&gt;Naomi Saphra discusses 5 rules governing language model behavior, breaking down why LLMs act like populations rather than individuals. She explains how tokenization creates strange semantic blind spots and highlights the mechanics of sycophancy, showing how models leverage subtle data associations to match user biases and demographics - even guessing political views based on favorite sports teams.&lt;/p&gt; &lt;i&gt;By Naomi Saphra&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>QCon AI 2025</category>
      <category>Large language models</category>
      <category>Transcripts</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Wed, 24 Jun 2026 11:25:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/5-principles-llm-behavior/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Naomi Saphra</dc:creator>
      <dc:date>2026-06-24T11:25:00Z</dc:date>
      <dc:identifier>/presentations/5-principles-llm-behavior/en</dc:identifier>
    </item>
    <item>
      <title>Article: Beyond CLEAN and MVP: Architecting an Offline-first Reactive Data Layer in Android</title>
      <link>https://www.infoq.com/articles/rdla-offline-first-reactive-android-data-layer/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/articles/rdla-offline-first-reactive-android-data-layer/en/headerimage/rdla-offline-first-reactive-android-data-layer-header-1781776366032.jpg"/&gt;&lt;p&gt;With the Reactive Data Layer Architecture (RDLA), you establish a clear boundary between public data APIs and private, framework-specific data-source implementations. Your presentation layer operates in a purely reactive manner, observing data changes rather than procedurally querying them. RDLA also simplifies testing by encouraging you to program to interfaces and use clean seeding patterns.&lt;/p&gt; &lt;i&gt;By Mervyn Anthony&lt;/i&gt;</description>
      <category>Android</category>
      <category>Reactive Programming</category>
      <category>Asynchronous Architecture</category>
      <category>MVP</category>
      <category>Clean Architecture</category>
      <category>Mobile</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>article</category>
      <pubDate>Wed, 24 Jun 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/rdla-offline-first-reactive-android-data-layer/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Mervyn Anthony</dc:creator>
      <dc:date>2026-06-24T09:00:00Z</dc:date>
      <dc:identifier>/articles/rdla-offline-first-reactive-android-data-layer/en</dc:identifier>
    </item>
    <item>
      <title>Lucide Releases Version 1.0, Removing Brand Icons and Cutting Bundle Size for Millions of Projects</title>
      <link>https://www.infoq.com/news/2026/06/lucide-v1-icons/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/06/lucide-v1-icons/en/headerimage/generatedHeaderImage-1782203932198.jpg"/&gt;&lt;p&gt;Lucide has released version 1.0 of its open-source icon toolkit, marking its first stable major release. The update features over 1,600 icons and removes trademarked brand icons due to legal and design concerns. Significant performance improvements have also been made, reducing package size and adding context providers for various frameworks. Users upgrading should be aware of breaking changes.&lt;/p&gt; &lt;i&gt;By Daniel Curtis&lt;/i&gt;</description>
      <category>Web Development</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Tue, 23 Jun 2026 13:28:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/lucide-v1-icons/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Daniel Curtis</dc:creator>
      <dc:date>2026-06-23T13:28:00Z</dc:date>
      <dc:identifier>/news/2026/06/lucide-v1-icons/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: The Time It Wasn't DNS</title>
      <link>https://www.infoq.com/presentations/incident-dns/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/presentations/incident-dns/en/mediumimage/sean-klein-medium-1781687984845.jpeg"/&gt;&lt;p&gt;Sean Klein discusses why "human error" is a dangerous myth in complex systems. Sharing the inside story of Azure’s 2023 global WAN outage, he explains how modern incident analysis looks past the "Five Whys" to uncover systemic issues. Learn how engineering leaders can move away from blame, improve Standard Operating Procedures, and design resilient systems that actively protect their engineers.&lt;/p&gt; &lt;i&gt;By Sean Klein&lt;/i&gt;</description>
      <category>QCon San Francisco 2025</category>
      <category>Incident Response</category>
      <category>Transcripts</category>
      <category>DevOps</category>
      <category>presentation</category>
      <pubDate>Tue, 23 Jun 2026 13:05:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/incident-dns/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Sean Klein</dc:creator>
      <dc:date>2026-06-23T13:05:00Z</dc:date>
      <dc:identifier>/presentations/incident-dns/en</dc:identifier>
    </item>
    <item>
      <title>Microsoft Expands Azure Kubernetes Service with Bare Metal, Fleet Management and AI Infrastructure</title>
      <link>https://www.infoq.com/news/2026/06/microsoft-build-aks-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/06/microsoft-build-aks-ai/en/headerimage/generatedHeaderImage-1782126504672.jpg"/&gt;&lt;p&gt;At this year's Microsoft Build 2026, Microsoft unveiled a broad set of enhancements to Azure Kubernetes Service (AKS) aimed at making Kubernetes a first-class platform for AI training, inference, and large-scale cloud-native applications.&lt;/p&gt; &lt;i&gt;By Craig Risi&lt;/i&gt;</description>
      <category>Kubernetes</category>
      <category>Microsoft</category>
      <category>Azure</category>
      <category>Artificial Intelligence</category>
      <category>Microsoft Azure</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Tue, 23 Jun 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/microsoft-build-aks-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Craig Risi</dc:creator>
      <dc:date>2026-06-23T12:00:00Z</dc:date>
      <dc:identifier>/news/2026/06/microsoft-build-aks-ai/en</dc:identifier>
    </item>
    <item>
      <title>AWS Launches Blocks, an Open-Source TypeScript Framework Designed for AI Agents to Build Backends</title>
      <link>https://www.infoq.com/news/2026/06/aws-blocks-framework-preview/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/06/aws-blocks-framework-preview/en/headerimage/generatedHeaderImage-1782118076693.jpg"/&gt;&lt;p&gt;AWS released Blocks in public preview, an open-source TypeScript framework where each Block bundles application code, local mocks, and AWS infrastructure. Designed for AI agents to write correct backends from the start, it runs locally without an AWS account and deploys the same code to Lambda, DynamoDB, Aurora, and Bedrock with zero changes.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>AI Architecture</category>
      <category>Cloud</category>
      <category>Infrastructure as Code</category>
      <category>Open Source Project Releases</category>
      <category>AWS</category>
      <category>Amazon Web Services</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Tue, 23 Jun 2026 09:15:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/aws-blocks-framework-preview/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Steef-Jan Wiggers</dc:creator>
      <dc:date>2026-06-23T09:15:00Z</dc:date>
      <dc:identifier>/news/2026/06/aws-blocks-framework-preview/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Challenging Google Analytics: Building a Scalable, Cost-Effective User Tracking Service</title>
      <link>https://www.infoq.com/presentations/mobile-user-tracking-service/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/presentations/mobile-user-tracking-service/en/mediumimage/alina-krasavina-medium-1781688348523.jpg"/&gt;&lt;p&gt;Alina Krasavina explains how Delivery Hero successfully deprecated Google Analytics and migrated to an internal user tracking platform. She discusses how a simplistic, highly scalable architecture allowed them to handle 10 times more load while capturing 97% of tracking data.&lt;/p&gt; &lt;i&gt;By Alina Krasavina&lt;/i&gt;</description>
      <category>InfoQ Dev Summit Munich 2025</category>
      <category>Data Analytics</category>
      <category>Transcripts</category>
      <category>Cross Platform</category>
      <category>Mobile</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>presentation</category>
      <pubDate>Mon, 22 Jun 2026 15:07:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/mobile-user-tracking-service/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Alina Krasavina</dc:creator>
      <dc:date>2026-06-22T15:07:00Z</dc:date>
      <dc:identifier>/presentations/mobile-user-tracking-service/en</dc:identifier>
    </item>
    <item>
      <title>Java News Roundup: Spring Tools, Helidon, Open Liberty, TomEE, JobRunr, Hibernate, Commonhaus</title>
      <link>https://www.infoq.com/news/2026/06/java-news-roundup-jun15-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/06/java-news-roundup-jun15-2026/en/headerimage/java-news-roundup-image-1782133635464.jpg"/&gt;&lt;p&gt;This week's Java roundup for June 15th, 2026, features news highlighting: point releases of Spring Tools, Helidon, JobRunr and Gradle; the June 2026 edition of Open Liberty; the first milestone release of Apache TomEE 11.0; the first beta release of Hibernate ORM 8.0; Quarkus emergency maintenance releases to address CVE-2026-50559; and four open-source projects join the Commonhaus Foundation.&lt;/p&gt; &lt;i&gt;By Michael Redlich&lt;/i&gt;</description>
      <category>Apache TomEE</category>
      <category>Open Liberty</category>
      <category>JDK 28</category>
      <category>Gradle</category>
      <category>Quarkus</category>
      <category>Hibernate ORM</category>
      <category>JobRunr</category>
      <category>Open JDK</category>
      <category>Commonhaus Foundation</category>
      <category>JDK 27</category>
      <category>Spring Framework</category>
      <category>Helidon</category>
      <category>Java</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Mon, 22 Jun 2026 13:15:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/java-news-roundup-jun15-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Michael Redlich</dc:creator>
      <dc:date>2026-06-22T13:15:00Z</dc:date>
      <dc:identifier>/news/2026/06/java-news-roundup-jun15-2026/en</dc:identifier>
    </item>
    <item>
      <title>Article: Understanding ML Model Poisoning: How It Happens and How to Detect It</title>
      <link>https://www.infoq.com/articles/understanding-ml-model-poisoning/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/articles/understanding-ml-model-poisoning/en/headerimage/header-understanding-ml-model-poisoning-1781597719189.jpg"/&gt;&lt;p&gt;In this article, the author explores data poisoning as a threat to machine learning systems, covering techniques such as label flipping, backdoors, clean-label poisoning, and gradient manipulation. The article reviews real-world incidents, discusses the challenges of detecting poisoned data, and presents practical defenses, tools, and operational practices for securing ML training pipelines.&lt;/p&gt; &lt;i&gt;By Igor Maljkovic&lt;/i&gt;</description>
      <category>AI Security</category>
      <category>Adversarial Machine Learning</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>article</category>
      <pubDate>Mon, 22 Jun 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/understanding-ml-model-poisoning/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Igor Maljkovic</dc:creator>
      <dc:date>2026-06-22T11:00:00Z</dc:date>
      <dc:identifier>/articles/understanding-ml-model-poisoning/en</dc:identifier>
    </item>
    <item>
      <title>Podcast: How eBPF Empowers Developers to Observe Inside the Linux Kernel in a Safe and Unintrusive Way</title>
      <link>https://www.infoq.com/podcasts/empowers-developers-inside-linux-kernel/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/podcasts/empowers-developers-inside-linux-kernel/en/smallimage/the-infoq-podcast-logo-thumbnail-1781614035659.jpg"/&gt;&lt;p&gt;Dan Fineran explores how eBPF has evolved far beyond its roots in packet filtering into a robust, safe way to extend the Linux kernel. He explains how the eBPF "verifier", the security guardrail, enables implementation of deep observability and networking without the risks of traditional kernel modules or the slow upstreaming process.&lt;/p&gt; &lt;i&gt;By Dan Fineran&lt;/i&gt;</description>
      <category>eBPF</category>
      <category>The InfoQ Podcast</category>
      <category>Observability</category>
      <category>Linux</category>
      <category>Security</category>
      <category>DevOps</category>
      <category>podcast</category>
      <pubDate>Mon, 22 Jun 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/podcasts/empowers-developers-inside-linux-kernel/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Dan Fineran</dc:creator>
      <dc:date>2026-06-22T11:00:00Z</dc:date>
      <dc:identifier>/podcasts/empowers-developers-inside-linux-kernel/en</dc:identifier>
    </item>
    <item>
      <title>AWS Graviton5 Reaches General Availability with 192 Cores and Formally Verified VM Isolation</title>
      <link>https://www.infoq.com/news/2026/06/aws-graviton5-ga/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/06/aws-graviton5-ga/en/headerimage/generatedHeaderImage-1781703289721.jpg"/&gt;&lt;p&gt;AWS made Graviton5-powered EC2 M9g and M9gd instances generally available with 192 ARM cores, formally verified VM isolation via the Nitro Isolation Engine, and DDR5-8800 memory. ClickHouse reported 36% better performance with zero code changes. Meta committed tens of millions of cores. On-demand pricing is 9% above Graviton4, translating to roughly 15% better price-performance.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>AI Architecture</category>
      <category>Cloud</category>
      <category>Cloud Architecture</category>
      <category>IaaS</category>
      <category>AWS</category>
      <category>Containers</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Mon, 22 Jun 2026 10:05:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/aws-graviton5-ga/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Steef-Jan Wiggers</dc:creator>
      <dc:date>2026-06-22T10:05:00Z</dc:date>
      <dc:identifier>/news/2026/06/aws-graviton5-ga/en</dc:identifier>
    </item>
    <item>
      <title>Anthropic Reports Claude Now Handles 95% of Internal Analytics Queries</title>
      <link>https://www.infoq.com/news/2026/06/anthropic-claude-analytics/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/06/anthropic-claude-analytics/en/headerimage/generatedHeaderImage-1781542483302.jpg"/&gt;&lt;p&gt;Anthropic recently reported that Claude now handles around 95% of its internal analytics requests, letting employees query business data independently instead of relying on data teams. The company attributes this result less to advances in models and more to data governance, semantic definitions, and operational discipline.&lt;/p&gt; &lt;i&gt;By Renato Losio&lt;/i&gt;</description>
      <category>Data Governance</category>
      <category>Claude</category>
      <category>Data Analytics</category>
      <category>Data Lake</category>
      <category>Anthropic</category>
      <category>Business Analytics</category>
      <category>Architecture &amp; Design</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Sun, 21 Jun 2026 16:47:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/anthropic-claude-analytics/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Renato Losio</dc:creator>
      <dc:date>2026-06-21T16:47:00Z</dc:date>
      <dc:identifier>/news/2026/06/anthropic-claude-analytics/en</dc:identifier>
    </item>
    <item>
      <title>Inside Atlassian’s Forge Billing Architecture for Distributed Usage Tracking at Scale</title>
      <link>https://www.infoq.com/news/2026/06/forge-billing-usage-platform/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/06/forge-billing-usage-platform/en/headerimage/generatedHeaderImage-1780198060365.jpg"/&gt;&lt;p&gt;Atlassian details the Forge billing platform built for usage-based pricing across its cloud ecosystem. It processes large-scale usage events with correct attribution, deduplication, and aggregation using a streaming pipeline, idempotent processing, and layered storage to enable accurate billing, near real-time visibility, and reliable reconciliation across distributed services.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Jira</category>
      <category>Apache Kafka</category>
      <category>SaaS</category>
      <category>Cloud Architecture</category>
      <category>Distributed Systems</category>
      <category>FinOps</category>
      <category>Observability</category>
      <category>Streaming</category>
      <category>Event Stream Processing</category>
      <category>Event Driven Architecture</category>
      <category>Atlassian</category>
      <category>Multi-tenancy</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sat, 20 Jun 2026 14:21:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/forge-billing-usage-platform/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-06-20T14:21:00Z</dc:date>
      <dc:identifier>/news/2026/06/forge-billing-usage-platform/en</dc:identifier>
    </item>
    <item>
      <title>Apple Launches Core AI for Apple-Silicon Optimized On-Device Generative AI</title>
      <link>https://www.infoq.com/news/2026/06/apple-core-ai-wwdc/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/06/apple-core-ai-wwdc/en/headerimage/jetbrains-rustrover-ide-1781953134950.jpeg"/&gt;&lt;p&gt;At WWDC 26, Apple announced the Core AI framework, the official successor to Core ML. It is designed to allow developers to run large language models and generative AI entirely on-device, supporting both custom-converted PyTorch models and pre-optimized open-source models.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>MacOS</category>
      <category>visionOS</category>
      <category>Python</category>
      <category>Artificial Intelligence</category>
      <category>iOS</category>
      <category>Large language models</category>
      <category>Apple</category>
      <category>Mobile</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Sat, 20 Jun 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/apple-core-ai-wwdc/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-06-20T11:00:00Z</dc:date>
      <dc:identifier>/news/2026/06/apple-core-ai-wwdc/en</dc:identifier>
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