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NVIDIA Details BioNeMo Inference Runtime (BioIR): 2.90x Higher Boltz-2 Folding Throughput and 58.5K Residues per GPU-Hour on 8xH100

NVIDIA released BioNeMo Inference Runtime (BioIR), an open-source PyTorch-compatible library delivering 2.90x higher Boltz-2 protein-folding throughput on 8xH100 GPUs.

NVIDIA detailed BioIR, a Python library that accelerates Boltz-2, OpenFold2, and OpenFold3 structure-prediction inference on NVIDIA GPUs while preserving standard PyTorch workflows. On a matched benchmark of 1,000 human dimers on 8xH100 80GB GPUs, BioIR delivered 58.5K folded residues per GPU-hour versus 20.2K for a torch.compile baseline, a 2.90x throughput gain. BioIR already powered the AlphaFold Database expansion, generating about 31 million candidate complexes across 4,777 proteomes, with 1.81 million released as high-confidence predictions. Extrapolated to 1 million targets, estimated folding energy drops from 35 MWh to 11 MWh at 8-GPU TDP equivalents.

MarkTechPost · 6d agoAI tools & infra1

Two CVSS 9.8 Auth Bypasses in miniOrange SAML WordPress Plugin Were Exploited Before Any Database Even Listed the Paid Editions as Vulnerable

Attackers actively exploit two CVSS 9.8 auth bypasses (CVE-2026-61979, CVE-2026-15981) in the miniOrange SAML WordPress plugin, forging SAML responses to become admin.

CVE-2026-61979 is a SAML algorithm confusion flaw that lets attackers sign forged assertions using the identity provider's RSA public key as an HMAC secret; CVE-2026-15981 stems from PHP treating openssl_verify()'s -1 error return as true, allowing a crafted signature that triggers an OpenSSL error to validate. Both bugs independently let unauthenticated attackers obtain WordPress administrator sessions and both are confirmed exploited in the wild. DigitalOcean discovered the exploitation via a network anomaly after public vulnerability databases covered only the Free edition (fixed in 5.4.5), leaving seven independently versioned paid editions appearing patched. Attackers are scanning SSO endpoints from six IPs in Belgium, Nigeria, the US and Germany, and paid-edition fixes require manual uploads across version lines.

Security Affairs · 22d agoExploit / PoC in the wildCVE-2026-61979CVE-2026-15981

Jev: New frontier model 40-400x cheaper and 20-200x faster

TypeSafe AI launches Jev, an early-access 'System One' model delivering calibrated structured outputs claimed 40-400x faster and cheaper than LLMs.

TypeSafe AI, founded by former OpenAI researcher Diogo Almeida, released its first 'System One Model' called Jev in early access. Jev forgoes string generation and is trained with Reinforcement Learning for Calibrated Decisions (RLCD) to produce type-safe structured values with calibrated probabilities. The company claims 70-500ms response times (40-200x faster), input pricing of $0.042 per million tokens, and free output tokens via a parallel sampling architecture. Target use cases include AI-powered workflows, real-time applications, and verification/guardrail tasks.