π AI & Education - Data Residency Guarantees for Law Firms
Law firms don't buy AI models. They buy: β Data residency guarantees β Zero subpoena surface β Court-grade audit trails NYT v. OpenAI docs unsealed this week. If your AI vendor's own data practices can't survive discovery, why trust them with client files? Privilege >
Key Points:
Data Residency Guarantees: Law firms require AI vendors to store and process client data within their own jurisdiction, ensuring compliance with local laws and regulations.
Zero Subpoena Surface: AI vendors must have a zero-subpoena surface, meaning they cannot be compelled to disclose client data to third parties, including law enforcement or government agencies.
Court-Grade Audit Trails: AI vendors must maintain court-grade audit trails, providing a transparent and tamper-evident record of all data processing activities.
Actionable Takeaway: Law firms should carefully evaluate AI vendors' data practices and ensure they meet the necessary standards for data residency, subpoena surface, and audit trails.
π Resources:
- Original source β
- Original source
- NYT v. OpenAI docs β
- Data residency guarantees for law firms
π€ AutoData - Reframing Pre-Training Data Selection as a Search Problem
AutoData reframes pre-training data selection as a search problemβno more hand-crafted heuristics. An LLM agent writes and tests Python selection algorithms, iterating 200 times overnight. The winning recipe cuts validation bpb from 0.9537 to 0.9521 (+5.6Ο) and boosts CORE from
Key Points:
Reframing Pre-Training Data Selection: AutoData uses a search-based approach to select pre-training data, eliminating the need for hand-crafted heuristics.
LLM Agent: An LLM agent is used to write and test Python selection algorithms, allowing for rapid iteration and improvement.
Validation Results: The winning recipe achieved a significant reduction in validation bpb and an increase in CORE.
Actionable Takeaway: Developers can use AutoData to improve their pre-training data selection process, leading to better model performance.
π Resources:
- Original source β
- Original source
- AutoData β
- Reframing pre-training data selection as a search problem
π Florida Geometry Teachers - Revised Florida B.E.S.T. Geometry Course
Florida geometry teachers: Explore our revised Florida B.E.S.T. Geometry course with free, standards aligned support for shapes, trigonometry, constructions, reasoning, and proof. See what is new:
Key Points:
Revised Florida B.E.S.T. Geometry Course: The revised course provides free, standards-aligned support for geometry topics, including shapes, trigonometry, constructions, reasoning, and proof.
Standards Alignment: The course is aligned with Florida state standards, ensuring that students receive a comprehensive education in geometry.
Free Support: The course provides free support for teachers, including lesson plans, activities, and assessments.
Actionable Takeaway: Teachers can use the revised course to improve their geometry instruction, leading to better student outcomes.
π Resources:
- Original source β
- Original source
- Florida B.E.S.T. Geometry course β
- Revised Florida B.E.S.T. Geometry course
π― Teaching and Learning Funding Call - Apply for Up to Β£10,000
The deadline for our teaching and learning funding call is fast approaching! Apply for up to Β£10,000 to help shape the future of education with #AI. Submit your application by 24 September! https:// ai.cam.ac.uk/calls/ai-for-t eaching/ β¦
Key Points:
Teaching and Learning Funding Call: The funding call provides up to Β£10,000 to support teaching and learning initiatives that incorporate AI.
Deadline: The deadline for applications is 24 September.
AI for Teaching: The funding call aims to support the development of AI-powered teaching and learning tools.
Actionable Takeaway: Educators and researchers can apply for funding to develop innovative AI-powered teaching and learning tools.
π Resources:
- Original source β
- Original source
- AI for Teaching funding call β
- Teaching and learning funding call
π Building a Smarter Literature Review Workflow
Learn how to build a smarter, faster literature review workflow using three of the most powerful tools available to researchers right now. Ilya Shabanov @Artifexx will show you how to use Litmaps, Zotero, and Obsidian together to discover literature, organize your notes, and
Key Points:
Smarter Literature Review Workflow: The article provides a step-by-step guide to building a smarter literature review workflow using Litmaps, Zotero, and Obsidian.
Litmaps: Litmaps is a tool for discovering literature and organizing notes.
Zotero: Zotero is a citation management tool that helps researchers organize their sources.
Obsidian: Obsidian is a note-taking tool that allows researchers to organize their notes and ideas.
Actionable Takeaway: Researchers can use the tools and techniques described in the article to improve their literature review workflow.
π Resources:
- Original source β
- Original source
- Litmaps β
- Building a smarter literature review workflow
π DeepSeek-V4.1-Flash - A New 552B-Parameter Multimodal Model
DeepSeek-V4.1-Flash is a new 552B-parameter multimodal model that redefines whatβs possible for long-context agents. It slashes KV cache size to just 890 bytes per token (4Γ smaller than before) using a blend of cross-layer sharing and ultra-low-precision FP4 caching. The result?
Key Points:
DeepSeek-V4.1-Flash: The model is a new 552B-parameter multimodal model that achieves significant improvements in long-context agents.
KV Cache Size Reduction: The model reduces KV cache size by 4Γ using cross-layer sharing and ultra-low-precision FP4 caching.
Performance Improvement: The model achieves significant performance improvements, including faster inference and better accuracy.
Actionable Takeaway: Developers can use the DeepSeek-V4.1-Flash model to improve the performance of their long-context agents.
π Resources:
- Original source β
- Original source
- DeepSeek-V4.1-Flash β
- DeepSeek-V4.1-Flash model
π Word of the Day - Legerdemain
#WordOfTheDay https:// thsr.us/Legerdemain - skillful use of one's hands when performing conjuring tricks. E.g. "The magician's #legerdemain left the audience in awe and wonder." Synonyms:Prestidigitation, Trickery, Sleight of Hand #Vocabulary #Synonyms
Key Points:
Legerdemain: Legerdemain refers to the skillful use of one's hands when performing conjuring tricks.
Synonyms: The synonyms for legerdemain include prestidigitation, trickery, and sleight of hand.
Example: The example sentence illustrates the use of legerdemain in a conjuring trick.
Actionable Takeaway: Learners can use the word legerdemain to describe the skillful use of one's hands in conjuring tricks.
π Resources:
- Original source β
- Original source
- Power Thesaurus β
- Legerdemain
π Learnitive - A Local-First Workflow for Education
Weβre moving toward a Local-First workflow, adding advanced LaTeX editing, Interactive Docs, and richer project-based learning tools. Your work stays under your control while Learnitive provides the browser-based tools around it. Learn. Write. Build.
Key Points:
Local-First Workflow: Learnitive is moving towards a local-first workflow, allowing users to maintain control over their work.
Advanced LaTeX Editing: The platform provides advanced LaTeX editing capabilities.
Interactive Docs: Learnitive offers interactive documentation tools.
Richer Project-Based Learning Tools: The platform provides richer project-based learning tools.
Actionable Takeaway: Educators and learners can use Learnitive to create and manage their educational content.
π Resources:
- Original source β
- Original source
- Learnitive β
- Learnitive platform
π Grateful - A Synonym for Thankful
https:// thsr.us/grateful If someone is "grateful", they feel thankful for something. E.g. "She is grateful for his love and support." #synonym #thesaurus #learnenglish #ielts
Key Points:
Grateful: Grateful is a synonym for thankful, referring to the feeling of being thankful for something.
Example: The example sentence illustrates the use of grateful in a sentence.
Synonyms: The synonyms for grateful include thankful, appreciative, and thankful.
Actionable Takeaway: Learners can use the word grateful to describe the feeling of being thankful.
π Resources:
- Original source β
- Original source
- Power Thesaurus β
- Grateful
π CodeSignal - Engaging Students with AI
How can hands-on learning spark studentsβ curiosity? Dr. Andrea Martin, Professor of Practice of AI and Business at @Loyola_NOLA , shares how the @CodeSignalCom platform engages students. Explore the new CodeSignal courses: https:// hbsp.harvard.edu/search?f-copyr ight_holder_display_name=CodeSignal&enableQuerySyntax=true&aq=%40source%3D%28product_metadata%2C+he_bundles%29&activeTab=products&cid=organic-social%7Cx%7C2026-09-16-new-codesignal-courses-quote%7Cnone%7Cprod-online-course%7Cunknown%7Cserp%7Csep2026 β¦
Key Points:
CodeSignal: CodeSignal is a platform that engages students with hands-on learning experiences.
Dr. Andrea Martin: Dr. Andrea Martin shares her insights on how CodeSignal engages students.
New CodeSignal Courses: The article highlights the new CodeSignal courses available for students.
Actionable Takeaway: Educators and learners can use CodeSignal to engage students with AI-powered learning experiences.
π Resources:
- Original source β
- Original source
- CodeSignal β
- CodeSignal platform
