BytePlus Recommend: Personalization powered by machine learningEnhance every step of the user journey with personalized recommendations BytePlus Recommend provides rich personalized experiences using the latest innovations in machine learning
Monolith: Real Time Recommendation System With Collisionless Embedding Table
Building a scalable and real-time recommendation system is vital for many businesses driven by time-sensitive customer feedback, such as short-videos ranking or online ads. Despite the ubiquitous adoption of production-scale deep learning frameworks like TensorFlow or PyTorch, these general-purpose frameworks fall short of business demands in recommendation scenarios for various reasons: on one ha
GitHub - bytedance/sonic: A blazingly fast JSON serializing & deserializing library
goversion: 1.17.1 goos: darwin goarch: amd64 cpu: Intel(R) Core(TM) i9-9880H CPU @ 2.30GHz BenchmarkEncoder_Generic_Sonic-16 32393 ns/op 402.40 MB/s 11965 B/op 4 allocs/op BenchmarkEncoder_Generic_Sonic_Fast-16 21668 ns/op 601.57 MB/s 10940 B/op 4 allocs/op BenchmarkEncoder_Generic_JsonIter-16 42168 ns/op 309.12 MB/s 14345 B/op 115 allocs/op BenchmarkEncoder_Generic_GoJson-16 65189 ns/op 199.96 MB
Lei LI
Lei Li Carnegie Mellon University Language Technology Institute Assistant Professor Research area: natural language processing, machine learning. Topics: Large Language Models LLM agent: code generation, tool use, cooperation, reasoning Security, Privacy, Copyright of LLMs Efficient LLM Systems Multilingual NLP machine translation speech translation AI for Science AI for Drug Discovery Protein Des
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Bytedance Announces A New Plugin That Utilizes Machine Learning For Audio Synthesis
