Srinivas Gandikota @gonsrini
Joined February 2015-
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The Mind Machines, 1978 (MIT/Bell Labs)
This movie was made by Bell Telephone and seen by millions as a short movie before the main feature. It would be impossible for any public company to even get through a committee meeting today.
This movie was made by Bell Telephone and seen by millions as a short movie before the main feature. It would be impossible for any public company to even get through a committee meeting today.
The cube every engineer would like to have: Arduino based Rubik's cube 🤖 [📹 caracubo]
Platform 9¾..🐕🐾😅
Over the last week, I have figured out how to do neural architecture search. Developers writing architectures by hand makes as much sense as writing assembly by hand. Even less, the suboptimality factor is orders of magnitude larger. Watch this space for more info.
Absolutely wild that this kind of thing works at all
Absolutely wild that this kind of thing works at all
Introduction to Apache Kafka Error Handling (Springboot) #apachekafka dev.to/tharindufdo/in…
Finetuning the latest phi3 model on a macbook? Why not! Check out my latest blog post which explains how you can finetune phi-3 on a macbook pro: huggingface.co/blog/abhishek/…
So, what does that mean in practice? The first thing you need to do to use DSPy effectively is to get some data with labels. Those labels can be almost any kind of label, but you need labels.
That system performs OPTIMIZATION. In order to optimize, you need to have a metric. In order to have a metric, you must have. away of defining "good". In order to define good, you've got to understand your problem. No shortcuts.
I love e-ink displays with Open Source hardware + AI magic.
Only 13% of data projects make it into Production. Data is not enough; you need: 1. A pipeline that connects to your data sources. 2. To train your models. 3. Build a UI fast enough to render the result and chart with millions of records. 4. Finally, deploy your product so…
Just read Apple's "OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework". Similar to the OLMo, it's refreshing to see an LLM paper that shares details discussing the architecture, training methods, and training data. Let's start with the…
This AI can read emotions better than you can. It was created by Hume (@hume_ai) an AI research lab developing models that can read your face and your voice with uncanny accuracy. Their hope is that models that can read your emotions will help create AI that optimizes for human…
Sri Kapaliswarar Temple, Mylapore - An ancient Siva Temple - belonging to Poonamalee Saivites - Controlled by @tnhrcedept by #FRAUD - from 1970s The Executive Officer functioning in the temple by Fraud on the Statute - takes extraordinary time to pay Music Artists - who…
Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs Categorizes and examines Chain-of-X (CoX) methods, which generalize the Chain-of-Thought prompting approach to enhance LLM capabilities across various components and application tasks. 📝arxiv.org/abs/2404.15676
8 minute time-lapse of lightning 📹dfuji1
Not bad! This is like 8574 out of 32000 (n_ctx) token count
Introducing an experimental Llama-3-8B-Instruct with 32k context-length in GGUF format: - A big thanks to @winglian for doing the through test - A big thanks to @nisten for running tests Available on @huggingface and @LMStudioAI huggingface.co/MaziyarPanahi/…
Introducing an experimental Llama-3-8B-Instruct with 32k context-length in GGUF format: - A big thanks to @winglian for doing the through test - A big thanks to @nisten for running tests Available on @huggingface and @LMStudioAI huggingface.co/MaziyarPanahi/… https://t.co/WJ4sbiRz30
Mozilla published a nice writeup on how llamafile helped them evaluate the quality of AI models and quantization formats. The writeup goes into detail on the code, costs, and has a heartwarming story on some history with the local LLaMA community. blog.mozilla.ai/local-llm-as-j…
wen👩🏻💻 @DS_Wen_
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g balaji phaneedra k @gurrambalajip
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Yashjeet Pratap Singh @yashjeetpratap
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Brij Mohan Jha (Modi .. @ibrijmohanJi
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Sudheer Minchu @Minchu_Sudheer
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Saranya G @gsaranya81
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Learn Awesome @Learn_Awesome
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Deepa @deepasoumitri
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Gigamon @gigamon
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Lucid Software @LucidSoftware
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Kundan Prasad @kundanp12345
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Dr.Aaditya Ojha(pt) @AadityaOjha10
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Ashfaqur Rahman @AshfaqurRahman_
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Cameron R. Wolfe, Ph... @cwolferesearch
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Blender 🔶 @Blender
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Bindu Reddy @bindureddy
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Everyday Sanskrit @EverydaySanskri
5K Followers 92 Following Learn everyday spoken Sanskrit with ease. It's ok if you get it wrong sometimes, just keep learning.
Coschool Ai @coschoolai
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Andrej Karpathy @karpathy
978K Followers 904 Following 🧑🍳. Previously Director of AI @ Tesla, founding team @ OpenAI, CS231n/PhD @ Stanford. I like to train large deep neural nets 🧠🤖💥
Sarat Chandrika @saratchandrika3
1 Followers 1 Following
John Bull @garius
64K Followers 1K Following Historian. Streamer. Tech Strategist. Editor of @lonrec. Servant of Napoleon. Orient fan. @[email protected]. Business: [email protected]
Telangana Weatherman @balaji25_t
82K Followers 89 Following I'm T. Balaji. Weather enthusiast & Btech Civil 3rd year student in JNTUH HYD. Follow me for weather updates of Telangana. Not affiliated to any official agency
Hyderabad Rains @Hyderabadrains
26K Followers 47 Following Hi Iam Raj,Weather Enthusiastic,Follow Me for Weather Forecasts,Rainfall Updates,Alerts⚠...! #Hyderabad & #Telangana. For Official Weather Forecast Follow IMD.
Prof. Feynman @ProfFeynman
1.4M Followers 0 Following A universe of atoms, an atom in the universe. Tribute to the great explainer. Tweets about Science and Wisdom. Portrait by L.V Patten.
Yvette Cendes @whereisyvette
19K Followers 976 Following Hungarian-American radio astronomer @CenterforAstro, alias /u/Andromeda321. Only person who's been to Everest Base Camp AND punched by a wild mountain gorilla
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Scientific Python @SciPyTip
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PVR Narasimha Rao @homam108
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Raj Vedam @RajVedam1
13K Followers 248 Following Thanks for stopping by! Look me up - YouTube for my talks on Indian Civilization; FB for my interests; LinkedIn for my CV. Samples of my astro-photography shown
Nilesh Nilkanth Oak �.. @NileshOak
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Saraswati Films @mmpandit
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ProductNation/iSPIRT @Product_nation
18K Followers 4K Following A mission-oriented, nonprofit, technology think-and-do tank, driving 30 years orbit shifts. Powered by no-greed and no-glory volunteering.
MIT CSAIL @MIT_CSAIL
298K Followers 22K Following MIT's Computer Science & Artificial Intelligence Laboratory (CSAIL). Media Inquiries: [email protected]
Carolyn Hodges 👩�.. @MsCarolynHodges
6K Followers 5K Following I'm a #UI and #UX Engineer at @TheDatamartInc with full-stack experience in product and design, frontend development and systems engineering.
Quinns @Quinns108
106K Followers 823 Following Writer & presenter on games. See me on Quinns Quest, People Make Games and Shut Up & Sit Down. [email protected] / [email protected]
LabVIEW @labview
16K Followers 3K Following #LabVIEW: an @NIglobal systems engineering software for applications that require test, measurement, and control with rapid access to hardware and data insights
MATLAB @MATLAB
97K Followers 902 Following MATLAB is a high-level language and interactive environment for numerical computation, visualization, and programming 🖥️ Follow us on Instagram @MATLAB
Kim-Leigh Pontin @KimLeighPontin
4K Followers 997 Following Art Manager at Meta Reality Labs. CD for #TheBookOfCreatures #StoryTrails + #CorpTopia - Studied DI @RCA (Speculative / Design Fiction) Views my own.
Bhandarkar Oriental R.. @BhandarkarI
40K Followers 105 Following Research in Indology & Oriental Studies I Library of Manuscripts & Rare Books I Est. 1917 I https://t.co/906uRP5SjM
Jon Erlichman @JonErlichman
403K Followers 102 Following Tech, stocks & business history. Anchor “The Open” 9-10am on @BNNBloomberg & “Bloomberg Markets” 1-2pm on @BloombergTV 💍 @carolinelesley
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73K Followers 16 Following A registered trust pursuing legal actions and initiatives to usher in an Indic RenaissanceThe Mind Machines, 1978 (MIT/Bell Labs)
This movie was made by Bell Telephone and seen by millions as a short movie before the main feature. It would be impossible for any public company to even get through a committee meeting today.
Once Upon a Honeymoon, 1956 (public domain)
The cube every engineer would like to have: Arduino based Rubik's cube 🤖 [📹 caracubo]
Over the last week, I have figured out how to do neural architecture search. Developers writing architectures by hand makes as much sense as writing assembly by hand. Even less, the suboptimality factor is orders of magnitude larger. Watch this space for more info.
Absolutely wild that this kind of thing works at all
GPT-4V picks up an object with my robot hand. 1 hour to setup 0 tuning. Using laptop camera. Output is wrist angles and grip type. #Robotics
Introduction to Apache Kafka Error Handling (Springboot) #apachekafka dev.to/tharindufdo/in…
Finetuning the latest phi3 model on a macbook? Why not! Check out my latest blog post which explains how you can finetune phi-3 on a macbook pro: huggingface.co/blog/abhishek/…
So, what does that mean in practice? The first thing you need to do to use DSPy effectively is to get some data with labels. Those labels can be almost any kind of label, but you need labels.
That system performs OPTIMIZATION. In order to optimize, you need to have a metric. In order to have a metric, you must have. away of defining "good". In order to define good, you've got to understand your problem. No shortcuts.
I love e-ink displays with Open Source hardware + AI magic.
Only 13% of data projects make it into Production. Data is not enough; you need: 1. A pipeline that connects to your data sources. 2. To train your models. 3. Build a UI fast enough to render the result and chart with millions of records. 4. Finally, deploy your product so…
Just read Apple's "OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework". Similar to the OLMo, it's refreshing to see an LLM paper that shares details discussing the architecture, training methods, and training data. Let's start with the…
This AI can read emotions better than you can. It was created by Hume (@hume_ai) an AI research lab developing models that can read your face and your voice with uncanny accuracy. Their hope is that models that can read your emotions will help create AI that optimizes for human…
Sri Kapaliswarar Temple, Mylapore - An ancient Siva Temple - belonging to Poonamalee Saivites - Controlled by @tnhrcedept by #FRAUD - from 1970s The Executive Officer functioning in the temple by Fraud on the Statute - takes extraordinary time to pay Music Artists - who…
Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs Categorizes and examines Chain-of-X (CoX) methods, which generalize the Chain-of-Thought prompting approach to enhance LLM capabilities across various components and application tasks. 📝arxiv.org/abs/2404.15676
8 minute time-lapse of lightning 📹dfuji1
Not bad! This is like 8574 out of 32000 (n_ctx) token count
Introducing an experimental Llama-3-8B-Instruct with 32k context-length in GGUF format: - A big thanks to @winglian for doing the through test - A big thanks to @nisten for running tests Available on @huggingface and @LMStudioAI huggingface.co/MaziyarPanahi/…
@MaziyarPanahi @Orwelian84 @winglian Just tested yours at q4km, and 19k input prompt, it works well, you're good
Mozilla published a nice writeup on how llamafile helped them evaluate the quality of AI models and quantization formats. The writeup goes into detail on the code, costs, and has a heartwarming story on some history with the local LLaMA community. blog.mozilla.ai/local-llm-as-j…
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