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ServiceNow AI Releases Apriel-1.5-15B-Thinker: An Open-Weights Multimodal Reasoning Model that Hits Frontier-Level Performance on a Single-GPU Budget Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” ServiceNow AI Research Lab has released Apriel-1.5-15B-Thinker, a 15-billion-parameter open-weights multimodal reasoning model trained with a data-centric mid-training recipe—continual pretraining followed by supervised fine-tuning—without reinforcement learning or preference optimization. The model attains an Artificial Analysis Intelligence Index score of 52 with 8x cost savings… Read More »ServiceNow AI Releases Apriel-1.5-15B-Thinker: An Open-Weights Multimodal Reasoning Model that Hits Frontier-Level Performance on a Single-GPU Budget Asif Razzaq Artificial Intelligence Category – MarkTechPost

Hilbert: Recursively Building Formal Proofs with Informal Reasoning Apple Machine Learning Research

​Large Language Models (LLMs) demonstrate impressive mathematical reasoning abilities, but their solutions frequently contain errors that cannot be automatically verified. Formal theorem proving systems such as Lean 4 offer automated verification with complete accuracy, motivating recent efforts to build specialized prover LLMs that generate verifiable… Read More »Hilbert: Recursively Building Formal Proofs with Informal Reasoning Apple Machine Learning Research

Barriers for Learning in an Evolving World: Mathematical Understanding of Loss of Plasticity Apple Machine Learning Research

​Deep learning models excel in stationary data but struggle in non-stationary environments due to a phenomenon known as loss of plasticity (LoP), the degradation of their ability to learn in the future. This work presents a first-principles investigation of LoP in gradient-based learning. Grounded in… Read More »Barriers for Learning in an Evolving World: Mathematical Understanding of Loss of Plasticity Apple Machine Learning Research

TASER: Translation Assessment via Systematic Evaluation and Reasoning Apple Machine Learning Research

​We introduce TASER (Translation Assessment via Systematic Evaluation and Reasoning), a metric that uses Large Reasoning Models (LRMs) for automated translation quality assessment. TASER harnesses the explicit reasoning capabilities of LRMs to conduct systematic, step-by-step evaluation of translation quality. We evaluate TASER on the WMT24… Read More »TASER: Translation Assessment via Systematic Evaluation and Reasoning Apple Machine Learning Research

How Hapag-Lloyd improved schedule reliability with ML-powered vessel schedule predictions using Amazon SageMaker Thomas Voss Artificial Intelligence

​[[{“value”:” This post is cowritten with Thomas Voss and Bernhard Hersberger from Hapag-Lloyd. Hapag-Lloyd is one of the world’s leading shipping companies with more than 308 modern vessels, 11.9 million TEUs (twenty-foot equivalent units) transported per year, and 16,700 motivated employees in more than 400… Read More »How Hapag-Lloyd improved schedule reliability with ML-powered vessel schedule predictions using Amazon SageMaker Thomas Voss Artificial Intelligence

Rox accelerates sales productivity with AI agents powered by Amazon Bedrock Santhan Pamulapati Artificial Intelligence

​[[{“value”:” This post was co-written with Shriram Sridharan, Taeuk Kang, and Santhosh Kumar Manavasi Lakshminarayanan from Rox. Rox is building a new revenue operating system for the applied AI era. Modern revenue teams rely on more data than ever before, such as Customer Relationship Management… Read More »Rox accelerates sales productivity with AI agents powered by Amazon Bedrock Santhan Pamulapati Artificial Intelligence

Liquid AI Released LFM2-Audio-1.5B: An End-to-End Audio Foundation Model with Sub-100 ms Response Latency Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Liquid AI has released LFM2-Audio-1.5B, a compact audio–language foundation model that both understands and generates speech and text through a single end-to-end stack. It positions itself for low-latency, real-time assistants on resource-constrained devices, extending the LFM2 family into audio while retaining a small footprint.… Read More »Liquid AI Released LFM2-Audio-1.5B: An End-to-End Audio Foundation Model with Sub-100 ms Response Latency Asif Razzaq Artificial Intelligence Category – MarkTechPost

MLPerf Inference v5.1 (2025): Results Explained for GPUs, CPUs, and AI Accelerators Michal Sutter Artificial Intelligence Category – MarkTechPost

​[[{“value”:” What MLPerf Inference Actually Measures? MLPerf Inference quantifies how fast a complete system (hardware + runtime + serving stack) executes fixed, pre-trained models under strict latency and accuracy constraints. Results are reported for the Datacenter and Edge suites with standardized request patterns (“scenarios”) generated… Read More »MLPerf Inference v5.1 (2025): Results Explained for GPUs, CPUs, and AI Accelerators Michal Sutter Artificial Intelligence Category – MarkTechPost