Anthropic disables Fable 5 and Mythos 5 as SpaceX moves to buy Cursor
· 10 stories · 41 sources
Written with AI, sources linked for every story
Anthropic has disabled Fable 5 and Mythos 5 worldwide following a US export-control directive. SpaceX has agreed to buy the company behind Cursor. Z.ai, Moonshot AI and MiniMax have released new models with open weights. Google, Adobe and Apple are also developing AI features that can carry out tasks in apps.
1Policy & regulationLaw & regulationCybersecurityEnterprise AI
Anthropic disables Fable 5 and Mythos 5 after US export directive
A US export-control directive restricted access for foreign nationals. Anthropic responded by disabling both models for customers worldwide.
Anthropic disabled Fable 5 and Mythos 5 for all customers worldwide after receiving a US Commerce Department export-control directive on June 12, 2026.12 According to the company, the directive required it to suspend access for foreign nationals, including those inside the United States.32 It was not an outright prohibition on the models for every customer; the worldwide shutdown was Anthropic’s response to the access restriction.31
US officials cited national security and cybersecurity concerns.43 Anthropic said officials had not publicly provided specifics and that, to its knowledge, the concern included an alleged technique for bypassing Fable 5’s safeguards.43 After reviewing a demonstration, Anthropic said it found only a small number of previously known, minor vulnerabilities. It said similar issues could be found using other publicly available models.4
What it means for companies
If you use Fable 5 or Mythos 5 in production, check affected workflows and switch to tested alternatives for now. Document which applications depend on access to either model before planning to use them again.
SpaceX agrees to acquire Cursor in $60 billion deal
SpaceX has agreed to buy the company behind the Cursor coding tool. A jointly developed coding model has not been confirmed.
On June 16, 2026, SpaceX agreed to acquire Anysphere, the company behind the Cursor coding tool.12 The all-stock deal values Anysphere at $60 billion, but the acquisition has not closed.12 Cursor is expected to become a SpaceX subsidiary when the transaction is completed.32
The agreement follows a previously negotiated purchase option. It would give SpaceX a larger role in AI-assisted software development, a market where Anthropic and OpenAI are also active.13 The reports do not confirm a jointly developed coding model or a specific plan to use SpaceX computing infrastructure for one.13 For companies, the potential change in ownership is more concrete than any new model platform.
What it means for companies
If your company uses Cursor, review contract terms and data handling after any closing. Do not plan around a joint coding model or SpaceX compute capacity yet.
The model targets long-running coding tasks and claims a one-million-token context window. Its weights are now available.
Z.ai introduced GLM-5.2 for long-running coding tasks and released the model weights on June 17. The company states that the model supports a context window of up to one million tokens and positions it for work on large software projects.12 GLM-5.2 is also available through an API.3
The large context window could let teams work with more code and documentation in a single task. Its availability for every use case needs checking, however: a separately named variant is associated with the one-million-token window.4 Z.ai reports improvements on coding tasks, but results depend on the evaluation used.1 The released weights also give companies an option to assess self-hosting, subject to compute requirements and license terms.15
What it means for companies
If you are considering GLM-5.2 for coding assistants, test it on your own repositories and longer tasks. Confirm which context variant you can access, then compare API costs with the requirements of self-hosting.
Google introduces AppFunctions for AI agents on Android
AppFunctions is designed to let AI agents execute app capabilities on users’ behalf. Gemini integration is not broadly available yet.
Google introduced AppFunctions on June 16, 2026, as a way for AI agents to discover and execute Android app capabilities on a user's behalf.12 Agents can access an app's local state directly to complete workflows within it.1 The accompanying Jetpack library launched in alpha, while Gemini integration is in private preview with trusted testers.12
For now, AppFunctions is a developer platform capability, not a broadly available way to control any app through Gemini.12 Companies considering support will need to decide which actions agents may perform and which local data those actions expose. Google offers an early access program to help developers prepare their apps, but has not said when Gemini integration will become more widely available.2
What it means for companies
If your company builds an Android app, identify which functions an agent should be allowed to invoke and what local data they expose. Test those workflows and set access boundaries before enabling them.
5Products & toolsAI agentsEnterprise AIWork & society
Adobe expands Creative Agent across five Creative Cloud apps
Adobe’s AI Assistant can handle multistep tasks in creative apps. The company also plans connections to major AI assistants.
On June 18, 2026, Adobe expanded its Creative Agent across Firefly and Creative Cloud.1 Its AI Assistant is available in public beta in Premiere, Photoshop, Illustrator, Frame.io, and InDesign.21 Adobe says it can coordinate multistep tasks through natural-language prompts, including organizing footage, renaming assets, and adjusting layouts.2
The expansion puts more emphasis on managing production workflows rather than generating individual assets alone.21 Adobe also plans to make its creative tools accessible through ChatGPT, Claude, Copilot, Gemini, and Slack, but the integrations are not all available at once.13 New assistant capabilities in the Firefly web app are available in beta.1 Adobe is also testing an updated studio workspace with limited initial access.1
What it means for companies
If your team uses Adobe apps, test repetitive organizing and layout tasks on low-risk projects first. Before rolling them out, check which features are available and which connections to external assistants you want to allow.
6Products & toolsChatbots & assistantsEnterprise AI
Apple announces dedicated Siri app and expanded AI features
Siri AI is designed to resume conversations, use personal context, and take actions in apps. Developers can test it now, with a user beta planned for later.
Apple announced Siri AI and a dedicated Siri app at WWDC on June 8.12 Developers can test the new features on iOS 27, iPadOS 27, macOS 27, and visionOS 27; a user beta is planned for later in 2026.13 Siri is designed to resume conversations and answer questions using personal context from messages, email, photos, and on-screen content.41
Siri AI is also intended to draw on web information and take actions in apps.53 Depending on the task, Apple will process requests on-device or through its private cloud systems.45 The overhaul is part of Apple's effort to catch up with competing AI assistants.5 Its reliability in everyday use remains to be tested in the broader beta. The announced app is not yet a generally released consumer product.12
What it means for companies
If you plan to use Siri in business workflows, test its app actions on low-risk tasks first. Check whether your team's devices, languages, and regions are supported before rolling it out.
Bezos-led Prometheus raises $12 billion for industrial AI
Prometheus announced a $12 billion funding round. The company aims to build AI systems for designing and manufacturing physical products.
Prometheus, led by Jeff Bezos and Vik Bajaj, announced a $12 billion funding round on June 11, 2026. Reports put its valuation at about $41 billion. The company aims to develop AI systems that help design and manufacture complex physical products, including jet engines and computers. Some of the funding is intended to expand computing capacity.123
That ambition puts Prometheus in engineering workflows where design and manufacturing are closely linked. Bezos describes the goal as an “artificial general engineer” for the physical world. It is not yet possible to assess publicly how well its systems perform these tasks: The coverage provides no verified benchmarks or date when customers can use a product. For now, the round establishes the scale of the investment rather than the practical value of the planned systems.24
What it means for companies
If you use AI in design or manufacturing, watch Prometheus but do not plan around an available product yet. Evaluate any future offering against specific tasks, test results, and computing and data requirements.
Moonshot AI releases Kimi K2.7 Code as an open-source model
The coding model is available through Kimi Code and the Kimi API. Moonshot reports higher benchmark scores while using fewer reasoning tokens.
Moonshot AI released Kimi K2.7 Code on June 12 as an open-source model for agentic coding. It is available through Kimi Code and the Kimi API. Cloudflare also added the model to Workers AI.12
Moonshot reports 30% lower reasoning-token use than K2.6 and a 21.8% higher score on Kimi Code Bench v2. Those figures come from the company; the available sources do not establish independent verification of the benchmark gains. Fewer reasoning tokens also do not necessarily mean an entire task runs 30% faster or costs 30% less. For companies, the release adds another option for coding agents, but its value depends on performance against their own tasks and repositories.34
What it means for companies
If you use coding agents, test the model on your own repositories and tasks. Measure the cost, runtime, and quality of completed changes alongside token use.
9ModelsOpen sourceImage, video & audioCoding & dev tools
MiniMax releases M3 weights with multimodal input
MiniMax M3 accepts text, images, and video. The company reports a one-million-token context window, and the model weights are available on Hugging Face.
MiniMax released the weights for MiniMax M3 on Hugging Face on June 12, 2026.12 The company describes M3 as accepting text, images, and video, and reports a one-million-token context window.1 According to NVIDIA, the model uses MiniMax Sparse Attention, with a prefiltering stage intended to reduce the cost associated with conventional quadratic attention.3
The combination of published weights, multimodal input, and a large context window could be useful for applications handling extensive documents or video.13 The reported context length has not been independently verified. Public materials also do not establish which serving conditions allow use of the full window.13 MiniMax’s benchmark results offer a starting point for evaluating performance, but teams should test the model on their own workloads.1
What it means for companies
If you plan to use M3 for long documents or video, test the context length available in your deployment. Check licensing terms, operating costs, and performance on your own tasks.
10Infrastructure & hardwareOpen sourceEnterprise AI
LMCache details open-source KV-cache layer for LLM serving
LMCache published new technical details about its open-source cache layer. Its claim of up to a tenfold speedup applies to high-reuse workloads, not all inference.
In mid-June, LMCache published technical details about its already available open-source KV-cache layer. A June 15 post explains how cache data moves in multiprocess deployments.1 On June 17, the project also presented an access path using GPUDirect Storage.2 LMCache works with inference engines such as vLLM to reuse stored intermediate results across requests.3
That reuse can shorten time to first token, especially when requests share substantial context. LMCache says the improvement can reach an order of magnitude in high-reuse scenarios. This is a conditional project claim, not a benchmark result that applies to every deployment.3 For operators, the practical benefit depends on how often content is requested again and which storage and transfer paths their infrastructure provides.31
What it means for companies
If you operate LLMs, first measure how often requests reuse the same context. Test LMCache with your inference engine and storage setup before factoring its claimed speedup into capacity plans.
Every week we analyze a wide range of AI sources, select the stories that matter most to companies and research each of them. The texts are written with AI assistance and link to the original sources. How our news agent works
AI NewsWeek 25, 2026 June 13 – 19, 2026
Written with AI, sources linked for every story · 10 stories · 41 sources
Anthropic disables Fable 5 and Mythos 5 as SpaceX moves to buy Cursor
Anthropic has disabled Fable 5 and Mythos 5 worldwide following a US export-control directive. SpaceX has agreed to buy the company behind Cursor. Z.ai, Moonshot AI and MiniMax have released new models with open weights. Google, Adobe and Apple are also developing AI features that can carry out tasks in apps.
1 Policy & regulation · Law & regulation · Cybersecurity · Enterprise AI
Anthropic disables Fable 5 and Mythos 5 after US export directive
A US export-control directive restricted access for foreign nationals. Anthropic responded by disabling both models for customers worldwide.
Anthropic disabled Fable 5 and Mythos 5 for all customers worldwide after receiving a US Commerce Department export-control directive on June 12, 2026.12 According to the company, the directive required it to suspend access for foreign nationals, including those inside the United States.32 It was not an outright prohibition on the models for every customer; the worldwide shutdown was Anthropic’s response to the access restriction.31
US officials cited national security and cybersecurity concerns.43 Anthropic said officials had not publicly provided specifics and that, to its knowledge, the concern included an alleged technique for bypassing Fable 5’s safeguards.43 After reviewing a demonstration, Anthropic said it found only a small number of previously known, minor vulnerabilities. It said similar issues could be found using other publicly available models.4
about 50 vetted organizations
Fable 5 became publicly accessible on June 9, 2026.5
Anthropic said it received the directive at 5:21 p.m. ET.1
The access restriction also covered Anthropic employees who were foreign nationals.2
Mythos 5 had been shared with about 50 vetted organizations.5
What it means for companies: If you use Fable 5 or Mythos 5 in production, check affected workflows and switch to tested alternatives for now. Document which applications depend on access to either model before planning to use them again.
2 Business & market · Coding & dev tools · Enterprise AI
SpaceX agrees to acquire Cursor in $60 billion deal
SpaceX has agreed to buy the company behind the Cursor coding tool. A jointly developed coding model has not been confirmed.
On June 16, 2026, SpaceX agreed to acquire Anysphere, the company behind the Cursor coding tool.12 The all-stock deal values Anysphere at $60 billion, but the acquisition has not closed.12 Cursor is expected to become a SpaceX subsidiary when the transaction is completed.32
The agreement follows a previously negotiated purchase option. It would give SpaceX a larger role in AI-assisted software development, a market where Anthropic and OpenAI are also active.13 The reports do not confirm a jointly developed coding model or a specific plan to use SpaceX computing infrastructure for one.13 For companies, the potential change in ownership is more concrete than any new model platform.
$60 billion Deal value
Closing is expected in Q3 2026, subject to regulatory approvals.32
Anysphere shareholders are set to receive SpaceX Class A shares.2
SpaceX had previously secured an option to buy Anysphere for $60 billion.34
What it means for companies: If your company uses Cursor, review contract terms and data handling after any closing. Do not plan around a joint coding model or SpaceX compute capacity yet.
3 Models · Coding & dev tools · AI agents · Open source
Z.ai releases GLM-5.2 open weights
The model targets long-running coding tasks and claims a one-million-token context window. Its weights are now available.
Z.ai introduced GLM-5.2 for long-running coding tasks and released the model weights on June 17. The company states that the model supports a context window of up to one million tokens and positions it for work on large software projects.12 GLM-5.2 is also available through an API.3
The large context window could let teams work with more code and documentation in a single task. Its availability for every use case needs checking, however: a separately named variant is associated with the one-million-token window.4 Z.ai reports improvements on coding tasks, but results depend on the evaluation used.1 The released weights also give companies an option to assess self-hosting, subject to compute requirements and license terms.15
1M tokens stated context window
The model has 744 billion total parameters, with 40 billion active.5
API input costs $1.40 per million tokens, according to listed pricing.3
Listed API output pricing is $4.40 per million tokens.3
Artificial Analysis scores it 51 on its Intelligence Index.5
What it means for companies: If you are considering GLM-5.2 for coding assistants, test it on your own repositories and longer tasks. Confirm which context variant you can access, then compare API costs with the requirements of self-hosting.
Google introduces AppFunctions for AI agents on Android
AppFunctions is designed to let AI agents execute app capabilities on users’ behalf. Gemini integration is not broadly available yet.
Google introduced AppFunctions on June 16, 2026, as a way for AI agents to discover and execute Android app capabilities on a user's behalf.12 Agents can access an app's local state directly to complete workflows within it.1 The accompanying Jetpack library launched in alpha, while Gemini integration is in private preview with trusted testers.12
For now, AppFunctions is a developer platform capability, not a broadly available way to control any app through Gemini.12 Companies considering support will need to decide which actions agents may perform and which local data those actions expose. Google offers an early access program to help developers prepare their apps, but has not said when Gemini integration will become more widely available.2
AppFunctions adds executable tools to Android's MCP model.12
An agent skill can generate Kotlin code and ADB commands for testing.12
Gemini Intelligence is planned for select advanced devices later this summer.3
What it means for companies: If your company builds an Android app, identify which functions an agent should be allowed to invoke and what local data they expose. Test those workflows and set access boundaries before enabling them.
5 Products & tools · AI agents · Enterprise AI · Work & society
Adobe expands Creative Agent across five Creative Cloud apps
Adobe’s AI Assistant can handle multistep tasks in creative apps. The company also plans connections to major AI assistants.
On June 18, 2026, Adobe expanded its Creative Agent across Firefly and Creative Cloud.1 Its AI Assistant is available in public beta in Premiere, Photoshop, Illustrator, Frame.io, and InDesign.21 Adobe says it can coordinate multistep tasks through natural-language prompts, including organizing footage, renaming assets, and adjusting layouts.2
The expansion puts more emphasis on managing production workflows rather than generating individual assets alone.21 Adobe also plans to make its creative tools accessible through ChatGPT, Claude, Copilot, Gemini, and Slack, but the integrations are not all available at once.13 New assistant capabilities in the Firefly web app are available in beta.1 Adobe is also testing an updated studio workspace with limited initial access.1
What it means for companies: If your team uses Adobe apps, test repetitive organizing and layout tasks on low-risk projects first. Before rolling them out, check which features are available and which connections to external assistants you want to allow.
Apple announces dedicated Siri app and expanded AI features
Siri AI is designed to resume conversations, use personal context, and take actions in apps. Developers can test it now, with a user beta planned for later.
Apple announced Siri AI and a dedicated Siri app at WWDC on June 8.12 Developers can test the new features on iOS 27, iPadOS 27, macOS 27, and visionOS 27; a user beta is planned for later in 2026.13 Siri is designed to resume conversations and answer questions using personal context from messages, email, photos, and on-screen content.41
Siri AI is also intended to draw on web information and take actions in apps.53 Depending on the task, Apple will process requests on-device or through its private cloud systems.45 The overhaul is part of Apple's effort to catch up with competing AI assistants.5 Its reliability in everyday use remains to be tested in the broader beta. The announced app is not yet a generally released consumer product.12
Conversation history is designed to sync privately across devices through iCloud.41
The first user beta will be limited to supported devices and English.3
Siri AI will not initially be available on EU iPhones or iPads, or in China.5
What it means for companies: If you plan to use Siri in business workflows, test its app actions on low-risk tasks first. Check whether your team's devices, languages, and regions are supported before rolling it out.
7 Business & market · Funding & deals · Enterprise AI
Bezos-led Prometheus raises $12 billion for industrial AI
Prometheus announced a $12 billion funding round. The company aims to build AI systems for designing and manufacturing physical products.
Prometheus, led by Jeff Bezos and Vik Bajaj, announced a $12 billion funding round on June 11, 2026. Reports put its valuation at about $41 billion. The company aims to develop AI systems that help design and manufacture complex physical products, including jet engines and computers. Some of the funding is intended to expand computing capacity.123
That ambition puts Prometheus in engineering workflows where design and manufacturing are closely linked. Bezos describes the goal as an “artificial general engineer” for the physical world. It is not yet possible to assess publicly how well its systems perform these tasks: The coverage provides no verified benchmarks or date when customers can use a product. For now, the round establishes the scale of the investment rather than the practical value of the planned systems.24
$12 billion New funding
Prometheus had previously raised $6.2 billion at launch.12
The new round brings total funding above $18 billion.12
Backers include JPMorgan Chase, Goldman Sachs, and BlackRock.12
DST Global, Arch Venture Partners, and Bezos also invested.12
What it means for companies: If you use AI in design or manufacturing, watch Prometheus but do not plan around an available product yet. Evaluate any future offering against specific tasks, test results, and computing and data requirements.
8 Models · Coding & dev tools · Open source · AI agents
Moonshot AI releases Kimi K2.7 Code as an open-source model
The coding model is available through Kimi Code and the Kimi API. Moonshot reports higher benchmark scores while using fewer reasoning tokens.
Moonshot AI released Kimi K2.7 Code on June 12 as an open-source model for agentic coding. It is available through Kimi Code and the Kimi API. Cloudflare also added the model to Workers AI.12
Moonshot reports 30% lower reasoning-token use than K2.6 and a 21.8% higher score on Kimi Code Bench v2. Those figures come from the company; the available sources do not establish independent verification of the benchmark gains. Fewer reasoning tokens also do not necessarily mean an entire task runs 30% faster or costs 30% less. For companies, the release adds another option for coding agents, but its value depends on performance against their own tasks and repositories.34
−30% Reasoning tokens, per Moonshot
The MoE model has 1 trillion total parameters and 32 billion active parameters per token.2
Cloudflare has offered Kimi K2.7 Code on Workers AI since June 12.2
Moonshot also reports an 11.0% gain on Program Bench.3
What it means for companies: If you use coding agents, test the model on your own repositories and tasks. Measure the cost, runtime, and quality of completed changes alongside token use.
9 Models · Open source · Image, video & audio · Coding & dev tools
MiniMax releases M3 weights with multimodal input
MiniMax M3 accepts text, images, and video. The company reports a one-million-token context window, and the model weights are available on Hugging Face.
MiniMax released the weights for MiniMax M3 on Hugging Face on June 12, 2026.12 The company describes M3 as accepting text, images, and video, and reports a one-million-token context window.1 According to NVIDIA, the model uses MiniMax Sparse Attention, with a prefiltering stage intended to reduce the cost associated with conventional quadratic attention.3
The combination of published weights, multimodal input, and a large context window could be useful for applications handling extensive documents or video.13 The reported context length has not been independently verified. Public materials also do not establish which serving conditions allow use of the full window.13 MiniMax’s benchmark results offer a starting point for evaluating performance, but teams should test the model on their own workloads.1
1M tokens Reported context length
M3 has about 428 billion parameters, with roughly 23 billion active per token.3
What it means for companies: If you plan to use M3 for long documents or video, test the context length available in your deployment. Check licensing terms, operating costs, and performance on your own tasks.
10 Infrastructure & hardware · Open source · Enterprise AI
LMCache details open-source KV-cache layer for LLM serving
LMCache published new technical details about its open-source cache layer. Its claim of up to a tenfold speedup applies to high-reuse workloads, not all inference.
In mid-June, LMCache published technical details about its already available open-source KV-cache layer. A June 15 post explains how cache data moves in multiprocess deployments.1 On June 17, the project also presented an access path using GPUDirect Storage.2 LMCache works with inference engines such as vLLM to reuse stored intermediate results across requests.3
That reuse can shorten time to first token, especially when requests share substantial context. LMCache says the improvement can reach an order of magnitude in high-reuse scenarios. This is a conditional project claim, not a benchmark result that applies to every deployment.3 For operators, the practical benefit depends on how often content is requested again and which storage and transfer paths their infrastructure provides.31
up to 10x faster first token, project claim
Support for Mamba/GDN hybrid models was announced on June 16.4
A setup guide shows how to use LMCache with vLLM without a GPU.3
LMCache describes cache paths involving system memory and disk.31
What it means for companies: If you operate LLMs, first measure how often requests reuse the same context. Test LMCache with your inference engine and storage setup before factoring its claimed speedup into capacity plans.