Kimi K2.6, the best-performing open-source model, achieves just 3.8% on Diamond, 16% on Main and 37% on Extended.
开源模型与闭源模型之间存在显著差距,最佳开源模型在三个难度级别上的表现均大幅落后。37%的分数在Extended集上仍远低于Claude Opus的51.8%,这突显了开源模型在代码质量评估上的挑战,但也缺乏与商业模型同等规模的训练数据支持。
Kimi K2.6, the best-performing open-source model, achieves just 3.8% on Diamond, 16% on Main and 37% on Extended.
开源模型与闭源模型之间存在显著差距,最佳开源模型在三个难度级别上的表现均大幅落后。37%的分数在Extended集上仍远低于Claude Opus的51.8%,这突显了开源模型在代码质量评估上的挑战,但也缺乏与商业模型同等规模的训练数据支持。
Mythos Preview has found what it estimates are 6,202 high- or critical-severity vulnerabilities in these projects (out of 23,019 in total)
在扫描的1000多个开源项目中,AI模型发现了总计23,019个漏洞,其中6,202个为高危或严重级别,占比约27%。这一数据表明开源软件的安全状况比许多人想象的更加脆弱,也证明了AI在代码审计方面的强大能力。
Mythos Preview has found what it estimates are 6,202 high- or critical-severity vulnerabilities in these projects (out of 23,019 in total)
这个数据点提供了AI模型在开源软件扫描中的具体表现,27%的漏洞被评估为高危或严重级别。这是一个相当高的比例,表明系统性软件中存在大量安全风险。然而,这是AI模型的估计值,需要后续人工验证,文章中提到的90.6%验证率表明AI的评估有一定准确性,但仍存在误报可能。
for - open source - world population data - Worldpop
for - data visualization - words in high dimensional space - Google tensorflow - open source data visualization - of words
Die Fossilindustrie finanziert seit Jahrzehten Universitäten und fördert damit Publikationen in ihrem Interesse, z.B. zu false solutions wie #CCS. Hintergrundbericht anlässlich einer neuen Studie: https://www.theguardian.com/business/article/2024/sep/05/universities-fossil-fuel-funding-green-energy
Studie: https://doi.org/10.1002/wcc.904
I wonder what a source of truth is -- not necessarily an SSOT for the customer/company data, which is what Salesforce could become.
In den Ländern, die sich in Paris 2015 einer Initiative gegen das Verbrennen von nicht genutztem Erdgas (flaring) angeschlossen hatten, wird das Verbrennen mit offener Flamme oft nur durch Verbrennung in geschlossenen Anlagen ersetzt, wie eine investigative journalistische Recherche ergab. Die Menge der Emissionen sinkt dadurch nicht wesentlich, aber diese Anlagen sind für Satelliten nicht äußerlich erkennbar. https://www.theguardian.com/environment/2024/may/02/methane-emissions-gas-flaring-hidden-satellite-monitors-oil-gas
Ressourcen für die Recherche zu Methan-Emissionen: https://gijn.org/resource/new-tools-investigate-methane-emissions/
Argument quality and fallacies. (n.d.). HackMD. Retrieved January 17, 2022, from https://hackmd.io/@scibehC19vax/argumentquality
Giglietto, F., Farci, M., Marino, G., Mottola, S., Radicioni, T., & Terenzi, M. (2022). Mapping Nefarious Social Media Actors to Speed-up Covid-19 Fact-checking. SocArXiv. https://doi.org/10.31235/osf.io/6umqs
Just because a dataset is publicly available doesn't mean that you can use it to build commercial AI software.
Center For Global Development. “Three New Estimates of India’s All-Cause Excess Mortality during the COVID-19 Pandemic.” Accessed August 11, 2021. https://cgdev.org/publication/three-new-estimates-indias-all-cause-excess-mortality-during-covid-19-pandemic.
Figueiras, Maria J., Jihane Ghorayeb, Mariana V. C. Coutinho, João Marôco, and Justin Thomas. ‘Levels of Trust in Information Sources as a Predictor of Protective Health Behaviors During COVID-19 Pandemic: A UAE Cross-Sectional Study’. Frontiers in Psychology 0 (2021). https://doi.org/10.3389/fpsyg.2021.633550.
McCabe, Stefan, Leo Torres, Timothy LaRock, Syed Arefinul Haque, Chia-Hung Yang, Harrison Hartle, and Brennan Klein. ‘Netrd: A Library for Network Reconstruction and Graph Distances’. ArXiv:2010.16019 [Physics], 29 October 2020. http://arxiv.org/abs/2010.16019.
Armeni, Kristijan, Loek Brinkman, Rickard Carlsson, Anita Eerland, Rianne Fijten, Robin Fondberg, Vera Ellen Heininga, et al. ‘Towards Wide-Scale Adoption of Open Science Practices: The Role of Open Science Communities’. MetaArXiv, 6 October 2020. https://doi.org/10.31222/osf.io/7gct9.
Welcome to a new ERA of reproducible publishing. (2020, August 24). ELife; eLife Sciences Publications Limited. https://elifesciences.org/labs/dc5acbde/welcome-to-a-new-era-of-reproducible-publishing
Supporting Open Science Data Curation, Preservation, and Access by Libraries. (n.d.). Retrieved 24 August 2020, from https://www.youtube.com/watch?v=SbmGWHpzAHs
Ed Conway on Twitter: “Breaking: UK government was routinely overstating the total number of people who’d been tested for #COVID19 by as many as 200,000 at the height of the coronavirus pandemic, according to new Sky News analysis.” / Twitter. (n.d.). Twitter. Retrieved July 17, 2020, from https://twitter.com/EdConwaySky/status/1281652670000844800
Burgess, M. G., Langendorf, R. E., Ippolito, T., & Pielke, R. (2020). Optimistically biased economic growth forecasts and negatively skewed annual variation [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/vndqr
An analyst’s job is never done – GSS. (n.d.). Retrieved July 3, 2020, from https://gss.civilservice.gov.uk/blog/an-analysts-job-is-never-done/
Willem, L., Hoang, T. V., Funk, S., Coletti, P., Beutels, P., & Hens, N. (2020). SOCRATES: An online tool leveraging a social contact data sharing initiative to assess mitigation strategies for COVID-19 [Preprint]. Epidemiology. https://doi.org/10.1101/2020.03.03.20030627
Views, R. (2020, June 3). More Select COVID-19 Resources. /2020/06/03/more-select-covid-19-resources/
Epidemiologische Abklärung am Beispiel COVID-19. (n.d.). AGES - Österreichische Agentur für Gesundheit und Ernährungssicherheit. https://www.ages.at/service/service-presse/pressemeldungen/epidemiologische-abklaerung-am-beispiel-covid-19/
UK Data for Assessing COVID-19 Activity. (n.d.). CEBM. Retrieved May 12, 2020, from https://www.cebm.net/covid-19/covid-19-uk-data-for-assessing-the-way-out-of-lockdown/
Corona Scholar: Scientific COVID-19 Knowledge
Coronavirus Pandemic (COVID-19) – the data. (n.d.). Our World in Data. Retrieved May 4, 2020, from https://ourworldindata.org/coronavirus-data
A lot of data resources
First sighting of Jupyter Notebook (that I recall).
Methodology The classic OSINT methodology you will find everywhere is strait-forward: Define requirements: What are you looking for? Retrieve data Analyze the information gathered Pivoting & Reporting: Either define new requirements by pivoting on data just gathered or end the investigation and write the report.
Etienne's blog! Amazing resource for OSINT; particularly focused on technical attacks.
all the data
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Data sharing over open-source platforms can create ambiguous rules about data ownership and publication authorship, or raise concerns about data misuse by others, thus discouraging liberal sharing of data.
Surprising mention of “open-source platforms”, here. Doesn’t sound like these issues are absent from proprietary platforms. Maybe they mean non-institutional platforms (say, social media), where these issues are really pressing. But the wording is quite strange if that is the case.
It doesn’t work if we think the people who disagree with us are all motivated by malice, or that our political opponents are unpatriotic. Democracy grinds to a halt without a willingness to compromise; or when even basic facts are contested, and we listen only to those who agree with us.
C'mon, civic technologists, government innovators, open data advocates: this can be a call to arms. Isn't the point of "open government" to bring people together to engage with their leaders, provide the facts, and allow more informed, engaged debate?
the critical role that big data open source projects play in the Internet of Things (IoT).
If we believe in equality, if we believe in participatory democracy and participatory culture, if we believe in people and progressive social change, if we believe in sustainability in all its environmental and economic and psychological manifestations, then we need to do better than slap that adjective “open” onto our projects and act as though that’s sufficient or — and this is hard, I know — even sound.