#survey #distillation #Transformer #attention #gen_ai #llm
A Practical Survey on Faster and Lighter Transformers
https://arxiv.org/abs/2103.14636v2
#postgres #graphdb #graphmode #hack
Postgres: The Graph Database You Didn't Know You Had
https://www.dylanpaulus.com/posts/postgres-is-a-graph-database/
A Practical Survey on Faster and Lighter Transformers
https://arxiv.org/abs/2103.14636v2
#postgres #graphdb #graphmode #hack
Postgres: The Graph Database You Didn't Know You Had
https://www.dylanpaulus.com/posts/postgres-is-a-graph-database/
#hybrid_deployment #security #octopus #teamcity #cloud_deployment #mlops #github #github_actions #configuration_as_code #CAC
https://www.youtube.com/watch?v=BXBGwG2YjCo&ab_channel=OctopusDeploy
#llm #hype ? #expectations #gen_ai
https://venturebeat.com/ai/gartner-hype-cycle-places-generative-ai-on-the-peak-of-inflated-expectations/?ref=dl-staging-website.ghost.io
https://www.youtube.com/watch?v=BXBGwG2YjCo&ab_channel=OctopusDeploy
#llm #hype ? #expectations #gen_ai
https://venturebeat.com/ai/gartner-hype-cycle-places-generative-ai-on-the-peak-of-inflated-expectations/?ref=dl-staging-website.ghost.io
YouTube
The Art of Balancing Cloud and On-Prem Deployments
James Chatmas joins @jbristowe during a webinar to demonstrate how Octopus Deploy solves hybrid deployment challenges by letting you deploy to the cloud, containers, and on-premises environments. In particular, he shows how Octopus integrates with your DevOps…
#cloud #ml
https://www.yotec.net/comparison-of-machine-learning-as-a-service-systems-amazon-microsoft-azure-google-cloud-ai-ibm-watson/
#prompt_engineering #llm #zero_shot #reasoning
https://arxiv.org/abs/2205.11916
https://www.yotec.net/comparison-of-machine-learning-as-a-service-systems-amazon-microsoft-azure-google-cloud-ai-ibm-watson/
#prompt_engineering #llm #zero_shot #reasoning
https://arxiv.org/abs/2205.11916
Yotec
Comparison of Machine Learning as a Service systems: Amazon, Microsoft Azure, Google Cloud AI, IBM Watson - Yotec
Enhancing Chain-of-Thoughts Prompting with Iterative Bootstrapping in Large Language Models
#prompt_engineering #llm #zero_shot / auto #CoT
https://arxiv.org/abs/2304.11657v2
Optimal operation of cryogenic calorimeters through deep reinforcement learning
G. Angloher, et al.
Max-Planck-Institut für Physik, Germany
https://arxiv.org/abs/2311.15147
#prompt_engineering #llm #zero_shot / auto #CoT
https://arxiv.org/abs/2304.11657v2
Optimal operation of cryogenic calorimeters through deep reinforcement learning
G. Angloher, et al.
Max-Planck-Institut für Physik, Germany
https://arxiv.org/abs/2311.15147
#llm #training #dpo #vs #rlhf #ppo #reinforcement_learning #rl #gen_ai #NeurIPS
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
https://arxiv.org/abs/2305.18290v2
#deepmind #mistral #team #dpo #benchmarks #moe #llm #gen_ai
Mixtral of experts. A high quality Sparse Mixture-of-Experts.
https://mistral.ai/news/mixtral-of-experts
#offline_rl #rl
Revisiting the Minimalist Approach to Offline Reinforcement Learning
https://arxiv.org/abs/2305.09836
#agi #gen_ai #benchmarks
Levels of AGI: Operationalizing Progress on the Path to AGI
https://arxiv.org/abs/2311.02462v2
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
https://arxiv.org/abs/2305.18290v2
#deepmind #mistral #team #dpo #benchmarks #moe #llm #gen_ai
Mixtral of experts. A high quality Sparse Mixture-of-Experts.
https://mistral.ai/news/mixtral-of-experts
#offline_rl #rl
Revisiting the Minimalist Approach to Offline Reinforcement Learning
https://arxiv.org/abs/2305.09836
#agi #gen_ai #benchmarks
Levels of AGI: Operationalizing Progress on the Path to AGI
https://arxiv.org/abs/2311.02462v2
arXiv.org
Revisiting the Minimalist Approach to Offline Reinforcement Learning
Recent years have witnessed significant advancements in offline reinforcement learning (RL), resulting in the development of numerous algorithms with varying degrees of complexity. While these...
#fingpt #rag #llm #gpt
https://arxiv.org/abs/2310.04027v1
#vectorstore #vectordb #benchmarks #features #comparison
(1)
https://zackproser.com/vectordatabases
(2)
https://zilliz.com/vector-database-benchmark-tool?database=ZillizCloud%2CMilvus%2CElasticCloud%2CPgVector%2CPinecone%2CQdrantCloud%2CWeaviateCloud&dataset=medium&filter=none%2Clow%2Chigh&tab=2
(3)
https://superlinked.com/vector-db-comparison
#fintech #use_case
https://arxiv.org/abs/2310.04027
https://arxiv.org/abs/2310.04027v1
#vectorstore #vectordb #benchmarks #features #comparison
(1)
https://zackproser.com/vectordatabases
(2)
https://zilliz.com/vector-database-benchmark-tool?database=ZillizCloud%2CMilvus%2CElasticCloud%2CPgVector%2CPinecone%2CQdrantCloud%2CWeaviateCloud&dataset=medium&filter=none%2Clow%2Chigh&tab=2
(3)
https://superlinked.com/vector-db-comparison
#fintech #use_case
https://arxiv.org/abs/2310.04027
arXiv.org
Enhancing Financial Sentiment Analysis via Retrieval Augmented...
Financial sentiment analysis is critical for valuation and investment decision-making. Traditional NLP models, however, are limited by their parameter size and the scope of their training...
#llm #gpt #cost #best_practice #RAG
ROUTELLM: LEARNING TO ROUTE LLMS WITH
PREFERENCE DATA
https://arxiv.org/pdf/2406.18665
Searching for Best Practices in Retrieval-Augmented
Generation
https://arxiv.org/pdf/2407.01219
ROUTELLM: LEARNING TO ROUTE LLMS WITH
PREFERENCE DATA
https://arxiv.org/pdf/2406.18665
Searching for Best Practices in Retrieval-Augmented
Generation
https://arxiv.org/pdf/2407.01219
#fingpt #rag #llm #gpt
https://arxiv.org/abs/2310.04027v1
#structured_output #vs #outlines #vs #mirascope #vs #instructor #langhchain #guidance
https://simmering.dev/blog/structured_output/
https://simmering.dev/blog/openai_structured_output/
#aws #team #sagemaker #genai #inference #better #autoscale #subminute #metrics #cloudwatch
https://aws.amazon.com/about-aws/whats-new/2024/07/amazon-sagemaker-faster-auto-scaling-generative-ai-models/
https://aws.amazon.com/blogs/machine-learning/amazon-sagemaker-inference-launches-faster-auto-scaling-for-generative-ai-models/
https://arxiv.org/abs/2310.04027v1
#structured_output #vs #outlines #vs #mirascope #vs #instructor #langhchain #guidance
https://simmering.dev/blog/structured_output/
https://simmering.dev/blog/openai_structured_output/
#aws #team #sagemaker #genai #inference #better #autoscale #subminute #metrics #cloudwatch
https://aws.amazon.com/about-aws/whats-new/2024/07/amazon-sagemaker-faster-auto-scaling-generative-ai-models/
https://aws.amazon.com/blogs/machine-learning/amazon-sagemaker-inference-launches-faster-auto-scaling-for-generative-ai-models/
arXiv.org
Enhancing Financial Sentiment Analysis via Retrieval Augmented...
Financial sentiment analysis is critical for valuation and investment decision-making. Traditional NLP models, however, are limited by their parameter size and the scope of their training...
#llm #open_ai #o1 #vs #deepseek #kimi
https://github.com/deepseek-ai/DeepSeek-R1/blob/main/DeepSeek_R1.pdf
https://www.youtube.com/watch?v=LYxQbgAUzsQ
https://x.com/deepseek_ai/status/1881318130334814301
https://x.com/DrJimFan/status/1881382618627019050
https://pandaily.com/kimi-k1-5-the-first-non-openai-model-to-match-full-powered-o1-performance/
https://github.com/MoonshotAI/Kimi-k1.5/blob/main/Kimi_k1.5.pdf
https://github.com/deepseek-ai/DeepSeek-R1/blob/main/DeepSeek_R1.pdf
https://www.youtube.com/watch?v=LYxQbgAUzsQ
https://x.com/deepseek_ai/status/1881318130334814301
https://x.com/DrJimFan/status/1881382618627019050
https://pandaily.com/kimi-k1-5-the-first-non-openai-model-to-match-full-powered-o1-performance/
https://github.com/MoonshotAI/Kimi-k1.5/blob/main/Kimi_k1.5.pdf
GitHub
DeepSeek-R1/DeepSeek_R1.pdf at main · deepseek-ai/DeepSeek-R1
Contribute to deepseek-ai/DeepSeek-R1 development by creating an account on GitHub.
#llm #openai #stem_cells
https://www.technologyreview.com/2025/01/17/1110086/openai-has-created-an-ai-model-for-longevity-science/
https://www.technologyreview.com/2023/03/08/1069523/sam-altman-investment-180-million-retro-biosciences-longevity-death/
https://www.youtube.com/watch?v=D43-YFauw58
https://www.technologyreview.com/2025/01/17/1110086/openai-has-created-an-ai-model-for-longevity-science/
https://www.technologyreview.com/2023/03/08/1069523/sam-altman-investment-180-million-retro-biosciences-longevity-death/
https://www.youtube.com/watch?v=D43-YFauw58
MIT Technology Review
OpenAI has created an AI model for longevity science
The company is making a foray into scientific discovery with an AI built to help manufacture stem cells.
For Developers
#stability_ai #team #deepseek #vs #openai #comments #forecast https://youtu.be/lY8Ja00PCQM?si=aChjauEHB0Qu_41z&t=1277
#edge #llm
https://www.androidauthority.com/openai-chatgpt-ai-device-sam-altman-3522517/
#openai #team #product
https://openai.com/index/introducing-deep-research/
https://www.androidauthority.com/openai-chatgpt-ai-device-sam-altman-3522517/
#openai #team #product
https://openai.com/index/introducing-deep-research/
Android Authority
Sam Altman and Jony Ive's future AI device could involve a lot less typing into ChatGPT
OpenAI's Sam Altman has acknowledged that the company is working on an AI device, and strongly hinted at a voice-first approach.
#LCLM #vs #RAG
In Defense of RAG in the Era of Long-Context Language Models
https://arxiv.org/pdf/2409.01666
#observability #opentelemetry #llm #traceloop #team
https://www.youtube.com/watch?v=KVgbERRPU4M
In Defense of RAG in the Era of Long-Context Language Models
https://arxiv.org/pdf/2409.01666
#observability #opentelemetry #llm #traceloop #team
https://www.youtube.com/watch?v=KVgbERRPU4M
https://blog.google/technology/google-deepmind/gemini-model-thinking-updates-march-2025/
#llm #new #sota #team #google #vs #openai
#MoLE #Phi #team #microsoft #multimodal
Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs
https://ritvik19.medium.com/papers-explained-322-phi-4-mini-phi-4-multimodal-2be1a69be78c
https://arxiv.org/abs/2503.01743
#llm #new #sota #team #google #vs #openai
#MoLE #Phi #team #microsoft #multimodal
Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs
https://ritvik19.medium.com/papers-explained-322-phi-4-mini-phi-4-multimodal-2be1a69be78c
https://arxiv.org/abs/2503.01743
Google
Gemini 2.5: Our most intelligent AI model
Gemini 2.5 is our most intelligent AI model, now with thinking.
#alibaba #team #qwen #llm
https://www.scmp.com/tech/big-tech/article/3304935/alibabas-qwen3-ai-model-coming-month-sources-say-bid-cement-industry-lead
https://www.scmp.com/tech/big-tech/article/3304935/alibabas-qwen3-ai-model-coming-month-sources-say-bid-cement-industry-lead
South China Morning Post
Alibaba’s Qwen3 AI model coming this month, sources say
The latest upgrade to the Qwen family of models will include a mixture-of-experts version and one with just 600 million parameters for mobile devices.
For Developers
#stability_ai #team #deepseek #vs #openai #comments #forecast https://youtu.be/lY8Ja00PCQM?si=aChjauEHB0Qu_41z&t=1277
#cpu #inference #llm #gen_ai
https://techcrunch.com/2025/04/16/microsoft-researchers-say-theyve-developed-a-hyper-efficient-ai-model-that-can-run-on-cpus/
https://techcrunch.com/2025/04/16/microsoft-researchers-say-theyve-developed-a-hyper-efficient-ai-model-that-can-run-on-cpus/
TechCrunch
Microsoft researchers say they've developed a hyper-efficient AI model that can run on CPUs | TechCrunch
Microsoft researchers have developed — and released — a hyper-efficient AI model that can run on CPUs, including Apple's M2.
#observability #llm #openLLMetry #opentelemetry #aws
https://aws.amazon.com/blogs/apn/elevating-llm-observability-with-amazon-bedrock-and-dynatrace/
#grafana #team #assistant #ai
https://www.youtube.com/watch?v=ETZnD483mHI
https://aws.amazon.com/blogs/apn/elevating-llm-observability-with-amazon-bedrock-and-dynatrace/
#grafana #team #assistant #ai
https://www.youtube.com/watch?v=ETZnD483mHI
Amazon
Elevating LLM Observability with Amazon Bedrock and Dynatrace | Amazon Web Services
In this post, we explain how Dynatrace provides end-to-end monitoring and visibility into generative AI applications utilizing Amazon Bedrock models allowing for comprehensive LLM observability.