
Meta shakes up the frontiers, open and closed
Meta’s Muse Spark Open leads a shift in American open-weight models, joined by Reflection’s Beam.
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Meta’s Muse Spark Open leads a shift in American open-weight models, joined by Reflection’s Beam.
The instruction-tuned text model activates 23.4B of 501.3B parameters and supports a 1M-token context.

Reflection announced Beam, a 501-billion-parameter open-weight MoE that activates 23 billion parameters per token.

Reflection introduced Beam, a 501-billion-parameter open-weight model for coding and agents.
Prompt2Skill builds and refines LLM skills from a task description without curated training data.
AREX-2 trains a Qwen3.8-27B agent on long-horizon reflective tasks, lifting research and coding benchmarks.
UMM-Reflection uses interleaved RL so unified models repair their own image generations.
Payara Server 7.2026.1.RC1 HTTP EJB endpoints rely on attacker-controlled reflection and JNDI lookups without authorization, enabling arbitrary EJB method invocation.
Paper models multi-agent LLM orchestration as a bilevel game, proving transcript-only gating limits and introducing grounded-memory SRMA.

Cloudflare's H1 2026 report records a 519% surge in hyper-volumetric DDoS attacks, driven by DNS and CLDAP reflection amid geopolitical tensions.
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