Customer-obsessed science
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August 26, 20265 min readDiscounting the opinions of LLM judges with highly correlated outputs ensures that panels of judges reflect a true diversity of perspectives. -
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The Build on Trainium program is a $110 million credit initiative supporting AI research at 30 universities including Stanford, UC Berkeley, UIUC, UCLA, CMU, and MIT, with a focus on Responsible AI.
The Antibody Developability Benchmark is powered by one of the most diverse antibody datasets in public literature, enabling transparent performance evaluation for AI-guided antibody design.
Challenge pushes teams to demonstrate measurable gains in secure-coding performance while building AI agents that advance real-world utility and reliability at scale.
Initiative will fund over 100 doctoral students researching machine learning, computer vision, and natural-language processing at nine universities.
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Interspeech 20202020Prosody Transfer (PT) is a technique that aims to use the prosody from a source audio as a reference while synthesizing speech. Fine-grained PT aims at capturing prosodic aspects like rhythm, emphasis, melody, duration, and loudness, from a source audio at a very granular level and transferring them when synthesizing speech in a different target speaker’s voice. Cur-rent approaches for fine-grained PT suffer
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Interspeech 20202020The speech recognition training data corresponding to digital voice assistants is dominated by wake-words. Training endto-end (E2E) speech recognition models without careful attention to such data results in sub-optimal performance as models prioritize learning wake-words. To address this problem, we propose a novel discriminative initialization strategy by introducing a regularization term to penalize
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Interspeech 20202020As a crucial part of Alexa products, our on-device keyword spotting system detects the wakeword in conversation and initiates subsequent user-device interactions. Convolutional neural networks (CNNs) have been widely used to model the relationship between time and frequency in the audio spectrum. However, it is not obvious how to appropriately leverage the rich descriptive information from device state
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Interspeech 20202020Acoustic Scene Classification (ASC) is a challenging task, as a single scene may involve multiple events that contain complex sound patterns. For example, a cooking scene may contain several sound sources including silverware clinking, chopping, frying, etc. What complicates ASC more is that classes of different activities could have overlapping sounds patterns (e.g. both cooking and dishwashing could have
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Interspeech 20202020State-of-the-art Acoustic Modeling (AM) techniques use long short term memory (LSTM) networks, and apply multiple phases of training on large amount of labeled acoustic data - initial cross-entropy (CE) training or connectionist temporal classification (CTC) training followed by sequence discriminative training, such as state-level Minimum Bayes Risk (sMBR). Recently, there is considerable interest in applying
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Gretchen Ertl
The program offers unrestricted funds and other resources to support research at academic institutions and non-profit organizations in areas that align with our mission.
A global university competition to drive secure innovation in generative AI technology, which focuses on responsible AI and large language model coding security.
Credit: Wolfram Scheible
We partner with particular academic organizations across the world for deep and sustained collaborations in multiple research areas of mutual interest.
Courtesy of Pai-Ling Yin
We hire world-class academics to work on large-scale technical challenges, while they continue to teach and conduct research at their universities.
