David Smooke
Smooke
AI & ML interests
data, software, news, currency, cryptocurrency, software development, llms, internet usage, software market shares, startup investment data, startup location data, hackernoon
Recent Activity
liked
a model
13 days ago
Datou1111/shou_xin
updated
a collection
19 days ago
Models Used in HackerNoon Publishing System
upvoted
a
collection
about 1 month ago
Trending Startup Data Based on Internet Traffic & Engagement
Articles
Organizations
Smooke's activity
posted
an
update
about 2 months ago
Post
1852
Check out The AI Writing Contest with
@BrightData
! https://www.contests.hackernoon.com/ai-writing-contest Cash prizes for innovative approaches to AI and LLM training. We publish blog posts, research papers, stories of side hustles, you name it.
Any story tagged #AI enters to win. Most recent stories: https://hackernoon.com/tagged/ai and RSS feed https://hackernoon.com/tagged/ai/feed
Couple of favorite recent posts we published:
Why Salesforce and Microsoft Are Battling for the Future of AI Agents https://hackernoon.com/why-salesforce-and-microsoft-are-battling-for-the-future-of-ai-agents
Decentralized AI Summit at MIT Votes OriginTrail As The Best Decentralized AI Project https://hackernoon.com/decentralized-ai-summit-at-mit-votes-origintrail-as-the-best-decentralized-ai-project
Studying is Overrated https://hackernoon.com/studying-is-overrated
Why Canβt AI Count Letters??? https://hackernoon.com/why-cant-ai-count-letters
The Paradox of AI: If It Can't Replace us, Is It Making Us Dumber? https://hackernoon.com/the-paradox-of-ai-if-it-cant-replace-us-is-it-making-us-dumber
How Does Human Memory Work? https://hackernoon.com/how-does-human-memory-work
Is AI Actually Writing Production-Ready Code? https://hackernoon.com/is-ai-actually-writing-production-ready-code
Our AI Coding Tool Went Viral, Then Everything Broke. This is What We Learned. https://hackernoon.com/our-ai-coding-tool-went-viral-then-everything-broke-this-is-what-we-learned
Startups of The Year: Meet the AI Industry https://hackernoon.com/startups-of-the-year-meet-the-ai-industry
Nobel Prize Winner Geoffrey Hinton Explores Two Paths to Intelligence in AI Lecture https://hackernoon.com/nobel-prize-winner-geoffrey-hinton-explores-two-paths-to-intelligence-in-ai-lecture
Comparing AI vs. Blockchain Hype https://hackernoon.com/comparing-ai-vs-blockchain-hype
The SaaS Apocalypse and How aI Will Give Birth to One-person Tech Giants https://hackernoon.com/the-saas-apocalypse-and-how-ai-wi
Any story tagged #AI enters to win. Most recent stories: https://hackernoon.com/tagged/ai and RSS feed https://hackernoon.com/tagged/ai/feed
Couple of favorite recent posts we published:
Why Salesforce and Microsoft Are Battling for the Future of AI Agents https://hackernoon.com/why-salesforce-and-microsoft-are-battling-for-the-future-of-ai-agents
Decentralized AI Summit at MIT Votes OriginTrail As The Best Decentralized AI Project https://hackernoon.com/decentralized-ai-summit-at-mit-votes-origintrail-as-the-best-decentralized-ai-project
Studying is Overrated https://hackernoon.com/studying-is-overrated
Why Canβt AI Count Letters??? https://hackernoon.com/why-cant-ai-count-letters
The Paradox of AI: If It Can't Replace us, Is It Making Us Dumber? https://hackernoon.com/the-paradox-of-ai-if-it-cant-replace-us-is-it-making-us-dumber
How Does Human Memory Work? https://hackernoon.com/how-does-human-memory-work
Is AI Actually Writing Production-Ready Code? https://hackernoon.com/is-ai-actually-writing-production-ready-code
Our AI Coding Tool Went Viral, Then Everything Broke. This is What We Learned. https://hackernoon.com/our-ai-coding-tool-went-viral-then-everything-broke-this-is-what-we-learned
Startups of The Year: Meet the AI Industry https://hackernoon.com/startups-of-the-year-meet-the-ai-industry
Nobel Prize Winner Geoffrey Hinton Explores Two Paths to Intelligence in AI Lecture https://hackernoon.com/nobel-prize-winner-geoffrey-hinton-explores-two-paths-to-intelligence-in-ai-lecture
Comparing AI vs. Blockchain Hype https://hackernoon.com/comparing-ai-vs-blockchain-hype
The SaaS Apocalypse and How aI Will Give Birth to One-person Tech Giants https://hackernoon.com/the-saas-apocalypse-and-how-ai-wi
reacted to
fdaudens's
post with π₯
4 months ago
Post
2904
π How The Washington Post Uses AI to Empower Journalists ππ°
An exciting new example in the world of AI-assisted journalism! The Post has developed an internal tool called "Hayatacker" that's enhancing in-depth reporting. Here's why it matters:
π₯ What it does:
β’ Extracts stills from video files
β’ Processes on-screen text
β’ Labels objects in images
π³οΈ First big project:
Analyzed 745 Republican campaign ads on immigration (Jan-Jun 2024)
π€ Human-AI collaboration:
β’ AI extracts and organizes data
β’ Reporters verify and analyze findings
π Thorough approach:
β’ Manual review of all 745 ads
β’ Reverse image searches when context is lacking
β’ Cross-referencing with AdImpact transcripts
π‘ Key insight from WaPo's Senior Editor for AI strategy Phoebe Connelly:
"The more exciting choice is putting AI in the hands of reporters early on in the process."
This tool showcases how AI can augment journalistic capabilities without replacing human insight and verification. It's a powerful example of technology enhancing, not replacing, traditional reporting skills.
π Read the full article and the methodology: https://www.washingtonpost.com/elections/interactive/2024/republican-campaign-ads-immigration-border-security/
An exciting new example in the world of AI-assisted journalism! The Post has developed an internal tool called "Hayatacker" that's enhancing in-depth reporting. Here's why it matters:
π₯ What it does:
β’ Extracts stills from video files
β’ Processes on-screen text
β’ Labels objects in images
π³οΈ First big project:
Analyzed 745 Republican campaign ads on immigration (Jan-Jun 2024)
π€ Human-AI collaboration:
β’ AI extracts and organizes data
β’ Reporters verify and analyze findings
π Thorough approach:
β’ Manual review of all 745 ads
β’ Reverse image searches when context is lacking
β’ Cross-referencing with AdImpact transcripts
π‘ Key insight from WaPo's Senior Editor for AI strategy Phoebe Connelly:
"The more exciting choice is putting AI in the hands of reporters early on in the process."
This tool showcases how AI can augment journalistic capabilities without replacing human insight and verification. It's a powerful example of technology enhancing, not replacing, traditional reporting skills.
π Read the full article and the methodology: https://www.washingtonpost.com/elections/interactive/2024/republican-campaign-ads-immigration-border-security/
posted
an
update
4 months ago
Post
601
Chomsky predicting LLMs in 1956, curated by Ryan Rhodes (Rutgers)
posted
an
update
6 months ago
Post
886
Started a list of LLMs used to make HackerNoon happen:
HackerNoon/models-used-in-hackernoon-publishing-system-668c56a0d10c3be5d338b805
HackerNoon/models-used-in-hackernoon-publishing-system-668c56a0d10c3be5d338b805
posted
an
update
6 months ago
Post
507
NEW #DecentralizeAI Writing Contest, by InternetComputer.org and HackerNoon.com! π https://www.contests.hackernoon.com/decentralize-ai-writing-contest π€ͺ
"Not going to beat centralized AI with more centralized AI." - Emad Mostaque
To enter, submit a blog post with the #decentralize-ai tag on HackerNoon.
"Not going to beat centralized AI with more centralized AI." - Emad Mostaque
To enter, submit a blog post with the #decentralize-ai tag on HackerNoon.
posted
an
update
7 months ago
Post
684
The three most used image generation models in the HackerNoon editor are Kandinsky 3.0, Stable Diffusion XL, and RealVisXL V3.0 Turbo.
ai-forever/Kandinsky3.0 stabilityai/stable-diffusion-xl-base-1.0 SG161222/RealVisXL_V3.0
Try out the HackerNoon writing experience here: https://app.hackernoon.com/new
ai-forever/Kandinsky3.0 stabilityai/stable-diffusion-xl-base-1.0 SG161222/RealVisXL_V3.0
Try out the HackerNoon writing experience here: https://app.hackernoon.com/new
reacted to
Tar9897's
post with π
7 months ago
Post
2204
I made Tenzin public. One use-case at least to predict stock market prices for high-frequency trading. Would love to see the response as well as feedback you have for us. Please understand that this only represents 5% of the codebase of Tenzin 1.0. We will share more models and use-cases based on the feedback we receive along with keeping in mind AI safety and ethics.
Have fun and go and make some money :)
Have fun and go and make some money :)
reacted to
MrOvkill's
post with β€οΈ
7 months ago
Post
1583
Hello!
I am studying PyTorch, and I made something that converged really well for something this simplistic. It isn't masterful, but i'd welcome feedback, improvements, suggestions, anything. Tell me it sucks and to take it down, I will, just wanted to share what i've spent the last 2 days crying to figure out.
https://colab.research.google.com/gist/SMeyersMrOvkill/625371e1816afb2163bdc4194ba74e93/scratchpad.ipynb
I am studying PyTorch, and I made something that converged really well for something this simplistic. It isn't masterful, but i'd welcome feedback, improvements, suggestions, anything. Tell me it sucks and to take it down, I will, just wanted to share what i've spent the last 2 days crying to figure out.
https://colab.research.google.com/gist/SMeyersMrOvkill/625371e1816afb2163bdc4194ba74e93/scratchpad.ipynb
reacted to
singhsidhukuldeep's
post with π
7 months ago
Post
1493
Every time a new model is released that is topping 10+ leaderboards on 50+ benchmarks... π
My brain goes... I will wait for the LMSYS Chatbot Arena results! π€
User-facing evaluation, such as Chatbot Arena, provides reliable signals but is costly and slow. π’
Now we have MixEval, a new open benchmark with a 96% correlation to LMSYS Chatbot Arena and Human preferences. π―
It comes with MixEval (4k samples) and MixEval Hard (1k samples) π
Can use GPT-3.5-Turbo or any other open-source models as Parser/Judge π€
It takes less than 6% of the time and cost of MMLU πΈ
As expected:
In open models: Qwen2 72B >> Llama 3 70B >> Mixtral 8x7B π
In Closed Models: GPT-4o >> Claude 3 Opus >> Gemini Pro π
Leaderboard: https://mixeval.github.io/ π
My brain goes... I will wait for the LMSYS Chatbot Arena results! π€
User-facing evaluation, such as Chatbot Arena, provides reliable signals but is costly and slow. π’
Now we have MixEval, a new open benchmark with a 96% correlation to LMSYS Chatbot Arena and Human preferences. π―
It comes with MixEval (4k samples) and MixEval Hard (1k samples) π
Can use GPT-3.5-Turbo or any other open-source models as Parser/Judge π€
It takes less than 6% of the time and cost of MMLU πΈ
As expected:
In open models: Qwen2 72B >> Llama 3 70B >> Mixtral 8x7B π
In Closed Models: GPT-4o >> Claude 3 Opus >> Gemini Pro π
Leaderboard: https://mixeval.github.io/ π
posted
an
update
7 months ago
Post
1060
GPT-4o is "Clearly Programmed to Feed Dudes' Egos" - Desi Lydic on the Daily Show. https://www.youtube.com/watch?v=eFkUOi_9140&t=301s
posted
an
update
8 months ago
Post
1816
NEW publishing hub for trending text model academic research papers broken down into open source technical blog posts β‘οΈ https://textmodels.tech
replied to
their
post
8 months ago
it's real and it makes me laugh!
posted
an
update
9 months ago
Post
2819
Spent the morning designing a super important product: SMALL LANGUAGE MODEL BABY ONESIE https://www.shop.hackernoon.com/all-merch/p/small-language-model-baby-onesie
replied to
their
post
9 months ago
And published with a recent photo
https://hackernoon.com/we-are-actively-taking-steps-to-not-become-a-wasteland-of-ais-musings-says-hackernoon-founderceo
replied to
their
post
9 months ago
posted
an
update
9 months ago
Post
1932
π π π In a recent AI Time Journal Interview, I was asked: How has HackerNoon leveraged AI to enhance its platform? and what lessons have you learned about AIβs role in spam creation and prevention?
https://HackerNoon.com uses AI and machine learning to improve grammar, translate stories, generate featured images, suggest possible headlines, (and note, I would love to hear what else you think we should use AI for!) . Maybe Clippy was ahead of its time? Writers have and will continue to have smart AI assistants. AI can not and should not replace the writer, but it should and can assist the writer and editor throughout the publishing process. We are documenting our approach to editorial at https://EditingProtocol.com. With the rise of LLMs, weβve seen an influx of AI story spam submissions. Other blogging platforms are hosting so many of these types of machine-generated stories right now. We are actively taking steps not to become a wasteland of AIβs musings. Because every story is reviewed before publication (with about half being rejected), I think our average story quality is higher than other blogging platforms. Every story submission automatically enters into plagiarism and AI writing detection. We highlight what sections are likely, possibly, and unlikely to be written by AI. Itβs all about confidence levels. Ultimately, human editors make the final call in interpreting the machinesβ reports.
https://HackerNoon.com uses AI and machine learning to improve grammar, translate stories, generate featured images, suggest possible headlines, (and note, I would love to hear what else you think we should use AI for!) . Maybe Clippy was ahead of its time? Writers have and will continue to have smart AI assistants. AI can not and should not replace the writer, but it should and can assist the writer and editor throughout the publishing process. We are documenting our approach to editorial at https://EditingProtocol.com. With the rise of LLMs, weβve seen an influx of AI story spam submissions. Other blogging platforms are hosting so many of these types of machine-generated stories right now. We are actively taking steps not to become a wasteland of AIβs musings. Because every story is reviewed before publication (with about half being rejected), I think our average story quality is higher than other blogging platforms. Every story submission automatically enters into plagiarism and AI writing detection. We highlight what sections are likely, possibly, and unlikely to be written by AI. Itβs all about confidence levels. Ultimately, human editors make the final call in interpreting the machinesβ reports.
reacted to
abhishek's
post with π€πβ€οΈ
11 months ago
Post
Happy to announce, brand new, open-source Hugging Face Competitions platform π Now, create a machine learning competition for your friends, colleagues or the world for FREE* and host it on Hugging Face: the AI community building the future. Creating a competition requires only two steps:
pip install competitions
, then run competitions create
and create competition by answering a few questions π₯ Checkout the github repo: https://github.com/huggingface/competitions and docs: https://hf.co/docs/competitions