Author: IBL News

IBL News | New York

Anthropic’s CEO, Dario Amodei, said this Monday that his company has “never advocated for a ban on open-weights models,” in an attempt to counter criticism emerging across the tech industry that the AI lab is trying to exert excessive control over the future of AI.

“Open-weights models that don’t have dangerous capabilities are a public good: they don’t cost anything besides the compute needed to run them, and they provide value to businesses, developers, and researchers,” he explained.

“We should instead focus on keeping powerful chips out of authoritarian hands, stopping industrial-scale distillation, and requiring safety testing of all sufficiently capable models, open and closed.”

Amodei published his views in a blog post after a coalition of leading companies, including Nvidia, Microsoft, Meta, and Palantir, released a letter late last week urging policymakers to avoid “premature restrictions” on open-weight models, which users can download, modify, and run on their own infrastructure.

Chinese startups currently dominate the market, and some government officials have started to weigh whether those models should be banned or restricted in the U.S.

In his post, Dario Amodei stated that his “primary concern is the risk that authoritarian governments—not solely the Chinese Communist Party (CCP), although the CCP is clearly the most capable threat—build AI models that are more powerful than those built by the US, and use them to achieve permanent military superiority or perpetrate incredibly deep repression of their own people. “

• “The most dangerous model may be one that is trained in secret and handed only to the People’s Liberation Army for use in drones and the Ministry of State Security for surveillance and repression.”

• “My secondary concern is the risk that powerful AI models may be misused to carry out cyberattacks or biological attacks, and may have serious alignment problems.”

• “Open-weights models—it does not matter whether they come from China or anywhere else—do potentially present a higher risk than closed models, because it is very difficult to apply guardrails to them or monitor their usage, and once weights are released, they cannot be withdrawn.”

• “We should not sell powerful chips or chipmaking equipment to China, and we should crack down on the rampant smuggling and workarounds used to obtain access to such chips.”

• “We should crack down on industrial-scale distillation operations. Distillation is a much more compute-efficient process than training models from scratch. It allows China to build much better models than its number of chips would ordinarily enable, and thus partially evade chip bans. Distillation does not allow the CCP to obtain equivalent or superior AI capabilities to the US, but it can bring the Chinese frontier to within a few months of the US frontier.”

• “All sufficiently capable models, open and closed, should go through mandatory safety testing. The best way to address threat #2 is to just directly test models for cyber, biological, and alignment risks before release. I think this idea is actually close to a consensus.”

Mikel Amigot, IBL News | Louisville, Kentucky

Over 3,000 educators, administrators, and edtech professionals gathered this week in Louisville, Kentucky, for InstructureCon 2026, Instructure’s flagship annual conference.

Under the theme “Education in the Making,” the three-day event (July 21–23, 2026) delivered keynote addresses from renowned thinkers, a sweeping product roadmap, the launch of a new AI venture studio, and a landmark survey on AI adoption in education.

With over 200 sessions, workshops, and meetups spanning artificial intelligence, workforce readiness, accessible design, and evolving learner needs, InstructureCon 2026 was both a display of technological ambition and a test of whether Instructure can rebuild the trust compromised by the cybersecurity breach that struck its Canvas LMS on April 25, 2026,

Instructure’s CEO, Steve Daly, addressed “the incident”, as they called the data breach caused by the criminal organization ShinyHunters, promising transparency, honest communication, and every effort to rebuild trust through consistent action.

The company announced two new practical security features: one to download courses and another to fully remove all non-essential data on Canvas LMS.

• “It will be a defense at every layer, annual verification, and external audits.”

• “There will be faster detection and remediation, more frequent external validation, and more open collaboration.”

However, “We cannot predict a world without zero incidents; future attacks, in fact, will be more frequent and damaging,” said Armin Molavi, Chief Marketing Officer [in the picture below].

Also, the week prior to the conference, Instructure assessed a separate security threat disclosed against ShareFile, the third-party platform being used for secure data delivery. The company emphasized the ShareFile issue “did not involve Canvas or any Instructure systems.”

Daly shared what Instructure described as “a bold vision for how education and technology can move forward together in a time of rapid change,” framing the company’s evolution “from a learning management system provider to a comprehensive, future-ready learning ecosystem.” He emphasized that the rate of technological and workforce change will continue to accelerate and positioned Instructure as the partner to help institutions navigate it.

In the opening of the conference, guest speaker Michael Horn, co-founder of the Clayton Christensen Institute for Disruptive Innovation and one of education’s most recognized voices, challenged the audience to rethink AI’s role in education, not merely as an efficiency tool, but as a force that can “restore what education was always supposed to be: connection, curiosity, and purpose.”

He argued that AI should liberate educators from administrative burden, freeing them to spend more time genuinely engaging with students.

The biggest talking point of Day 1 was Instructure’s new research on the state of AI in education. Covering 1,125 respondents across educators, higher education students, and K-12 parents and guardians, the survey revealed a stark adoption gap:

• 90% of higher education students use AI in the classroom at least occasionally
• 61% of college instructors and 68% of K-12 educators also use AI in class
• Yet 41% of higher ed instructors and 45% of K-12 educators have received zero formal AI training
• Only 11% of college instructors reported comprehensive AI preparation; only 8% of K-12 educators
• 65% of all respondents worry that AI “presents incorrect information confidently”

Chief Learning Officer Melissa Loble framed these findings as validation for its IgniteAI strategy—embedding AI tools directly into existing Canvas workflows so educators can benefit from AI without needing to become AI specialists themselves.

On the second day of the conference, Instructure announced the launch of Instructure Foundry, a standalone venture studio within Instructure dedicated to innovation by developing “AI-native” educational products outside the traditional Canvas roadmap.

Designed to move faster than the core product team and experiment with ideas that don’t fit neatly into a learning management system, Foundry represents Instructure’s bet that the future of edtech requires startup-speed innovation backed by institutional-scale infrastructure.

Foundry’s inaugural project is Project Athena, an AI-powered study coach that delivers in-context learning through Canvas. Unlike generic AI tutoring tools, which operate without awareness of a student’s specific academic context, Athena pulls from a student’s actual Canvas environment — syllabi, course materials, assignments, and upcoming assessments — to generate:

• Personalized quizzes tailored to what the student is currently studying.
• Custom study guides aligned with real deadlines and assessment schedules.
• Coaching prompts that push toward mastery and deep understanding, not surface-level answers.

Chief Product Officer Shiren Vijiasingam emphasized that Athena addresses a “context gap” that plagues existing AI tutoring tools.  “Most AI tutoring tools have a critical gap: they generate explanations without the context of what students are actually learning and require students to find, organize, and upload course materials themselves,” he said.

On the sensitive topic of data privacy — particularly acute given the breach — Instructure was explicit: student conversations with Athena will not be used to train external AI models, access to Canvas data will be read-only and governed by existing user authorizations, and students retain full ownership of their data.

During the event, the Canvas LMS Product Roadmap was announced

Vijiasingam said, “Educational technology, powered by AI, can strengthen the connection between educator and student, amplify the voice and impact of the educator, and provide a personalized learning experience that improves student success.”

He added that AI-driven efficiency should translate into “time savings that allow educators to use their time in higher quality and more meaningful ways, spending it where it matters most.”

Instructure announced plans to update more than 20 key Canvas workflows throughout 2026, including:

• Course dashboards — customizable views for learners and educators, with mobile improvements to help students quickly identify priorities.
• Content creation — elevated tools with embedded accessibility checks and AI-assisted support directly within course design workflows.
• Course navigation — simplified flows and modernized interfaces.
• Grading processes — performance and usability upgrades for SpeedGrader, including improvements for large-enrollment courses.
• Media experiences — interactive transcripts, improved video navigation, and richer Canvas Studio integration. Institutions will have control over enabling changes at their own pace.
• Canvas Career, which reached general availability on January 29, 2026, was highlighted as Instructure’s purpose-built platform for workforce-aligned, skills-first education.
• Canvas Studio, Instructure’s video learning platform, received several enhancements:
  — Distraction-free YouTube integration with enhanced data privacy.
  — Video annotation capabilities for both instructors and students.
  — Vimeo upload support and automatic Zoom recording storage.
  — Account-level and course-level analytics with CSV export options.
  — Planned improvements for interactive transcripts and enhanced video navigation.

The Canvas platform owner concluded that the LMS — already the place where courses, grades, and student data live — is the natural home for AI in education.

By embedding AI directly into Canvas rather than building standalone products, Instructure is arguing that AI works best when it has context, and no tool has more educational context than the learning management system.