Mastodawn

Eddi Solar PV Diverter Top-up Dataset - Various stats for PV diversion and low-carbon-grid top-up of Sunamp Thermino. #heatBattery #microgen #dataset - https://m.earth.org.uk/eddi-diverter-dataset.html

Eddi Solar PV Diverter Top-up Dataset

Various stats for PV diversion and low-carbon-grid top-up of Sunamp Thermino. #heatBattery #microgen #dataset

sayzard 1d ago

Artificial Analysis (@ArtificialAnlys)

AA-WER v2.0, AA-AgentTalk 및 정제된 데이터셋에 대한 자세한 자료를 안내합니다. 블로그 포스트와 전체 결과 페이지 링크가 제공되며, Hugging Face에 공개된 VoxPopuli-Cleaned-AA 및 Earnings22-Cleaned-AA 정제 데이터셋도 확인할 수 있습니다. 연구/평가 재현과 데이터 접근을 위한 참고 링크입니다.

https://x.com/ArtificialAnlys/status/2024157412065001748

#aawer #speechtotext #huggingface #dataset #artificialanalysis

Artificial Analysis (@ArtificialAnlys) on X

For full details on AA-WER v2.0, AA-AgentTalk, and cleaned datasets: Blog post: https://t.co/x32f0v21AW Full results breakdown: https://t.co/AT8VlMgTM5 VoxPopuli-Cleaned-AA on Hugging Face: https://t.co/uB6TXhCET3 Earnings22-Cleaned-AA on Hugging Face: https://t.co/WywnCI3RFP

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sayzard 1d ago

Artificial Analysis (@ArtificialAnlys)

AA-WER v2.0 음성 인식(Speech-to-Text) 정확도 벤치마크와 음성 에이전트(voice agents)에 초점을 맞춘 신규 비공개 데이터셋 AA-AgentTalk를 발표했습니다. AA-AgentTalk은 음성 에이전트에 중요한 발화에 집중한 홀드아웃 데이터로, 음성비서류 모델 평가의 신뢰도와 실용성을 높이기 위해 설계되었습니다.

https://x.com/ArtificialAnlys/status/2024157398139883729

#speechtotext #benchmark #dataset #aawer #voiceagents

Artificial Analysis (@ArtificialAnlys) on X

Announcing AA-WER v2.0 Speech to Text accuracy benchmark, and AA-AgentTalk, a new proprietary dataset focused on speech directed at voice agents AA-AgentTalk focuses on the speech that matters most to voice agents. As a held-out, proprietary dataset, AA-AgentTalk also mitigates

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Earth Notes 2d ago

On 16WW Data Collections and Graphs - Open for research home #dataset - https://m.earth.org.uk/note-on-data.html

On 16WW Data Collections and Graphs

Open for research home #dataset

sayzard 6d ago

Onur Solmaz (@onusoz)

levelsio 등 사용자가 공개적으로 AI 응답을 표시(flag)하는 사례들이 오픈 데이터셋 'janitr_ai'의 주석(annotations)용 샘플로 활용될 수 있음을 제안하는 트윗입니다. 'blocked for ai reply' 같은 문구로 손쉽게 초기 학습 데이터 시드 샘플을 찾을 수 있다고 언급합니다.

https://x.com/onusoz/status/2022448101961687260

#dataset #annotations #janitr_ai #aidetection

Onur Solmaz (@onusoz) on X

The good thing about @levelsio and others flagging AI replies in public is that they are perfect annotations for the open @janitr_ai dataset Just searching “blocked for ai reply” yields hundreds of samples for seed data

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Earth Notes Feb 13

On 16WW Mains Inlet Water Temperature - Domestic mains water temperature data for 16WW on tap; seasonal min/max about 10C/20C in winter/summer. #dataset #water #temperature - https://m.earth.org.uk/note-on-data-for-16WW-mains-water-inlet-temperature.html

On 16WW Mains Inlet Water Temperature

Domestic mains water temperature data for 16WW on tap; seasonal min/max about 10C/20C in winter/summer. #dataset #water #temperature

Earth Notes Feb 12

16WW Energy Series Dataset - Time series of electricity and gas and other energy generation and use. #energy #microgen #dataset - https://m.earth.org.uk/energy-series-dataset.html

16WW Energy Series Dataset

Time series of electricity and gas and other energy generation and use. #energy #microgen #dataset

ERROR 404 ▼Feb 11

⭕Répertorié sous l’intitulé « EFTA01681865.pdf – #DataSet 10 », ce fichier provenait d’une présentation transmise par la #Deutsche_Bank au procureur de #New-York.

RE: https://bsky.app/profile/did:plc:2cte4wipyk47qjujtxrskqcx/post/3memfal2k7s2v

sayzard Feb 11

Jay Sensei (@hckinz)

Seedance 2.0이 배우 Rishab Shetty(@shetty_rishab)의 일부 영상으로 학습된 것처럼 보인다는 관찰이 제기되었다. 특정 장면을 테스트했더니 전사의 모습이 Rishab을 닮았다고 보고되어, 학습 데이터 출처·초상권·합성 결과 관련 우려가 제기된다.

https://x.com/hckinz/status/2021593945474470372

#seedance2 #dataset #privacy #deepfake

Jay Sensei👾 (@hckinz) on X

It seems seedance 2.0 trained on few footage of @shetty_rishab Kantara. tested this scene but the warrior look like Rishab 🫠

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sayzard Feb 11

Ai2 (@allen_ai)

LLM은 현실 작업(예: 세금신고)이나 AI 에이전트 계획 등 단계별 지침을 자주 생성하지만, 유창해 보여도 동작하지 않는 단계가 나오고 현재 데이터셋은 다루는 도메인이 제한적이라 개선이 어렵다. How2Everything은 이러한 단계별 지침 문제를 대규모로 평가하고( 및 훈련) 해결하기 위한 평가/데이터셋 솔루션을 제시한다.

https://x.com/allen_ai/status/2021264352175648956

#llm #how2everything #dataset #evaluation

Ai2 (@allen_ai) on X

LLMs often generate step-by-step instructions, from real-world tasks (how do I file taxes?) to plans for AI agents. Improving this is hard: outputs can sound fluent for steps that don't work, and current datasets cover few domains. How2Everything evals/trains for this at scale.

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