Seshu Adunuthula

1.9K posts

Seshu Adunuthula

Seshu Adunuthula

@SeshuAd

Data Engineering @ Intuit, @USC Parent, Weekend bicyclist.

San Jose, CA Katılım Ekim 2011
576 Takip Edilen334 Takipçiler
Seshu Adunuthula retweetledi
Andrej Karpathy
Andrej Karpathy@karpathy·
A number of people are talking about implications of AI to schools. I spoke about some of my thoughts to a school board earlier, some highlights: 1. You will never be able to detect the use of AI in homework. Full stop. All "detectors" of AI imo don't really work, can be defeated in various ways, and are in principle doomed to fail. You have to assume that any work done outside classroom has used AI. 2. Therefore, the majority of grading has to shift to in-class work (instead of at-home assignments), in settings where teachers can physically monitor students. The students remain motivated to learn how to solve problems without AI because they know they will be evaluated without it in class later. 3. We want students to be able to use AI, it is here to stay and it is extremely powerful, but we also don't want students to be naked in the world without it. Using the calculator as an example of a historically disruptive technology, school teaches you how to do all the basic math & arithmetic so that you can in principle do it by hand, even if calculators are pervasive and greatly speed up work in practical settings. In addition, you understand what it's doing for you, so should it give you a wrong answer (e.g. you mistyped "prompt"), you should be able to notice it, gut check it, verify it in some other way, etc. The verification ability is especially important in the case of AI, which is presently a lot more fallible in a great variety of ways compared to calculators. 4. A lot of the evaluation settings remain at teacher's discretion and involve a creative design space of no tools, cheatsheets, open book, provided AI responses, direct internet/AI access, etc. TLDR the goal is that the students are proficient in the use of AI, but can also exist without it, and imo the only way to get there is to flip classes around and move the majority of testing to in class settings.
Andrej Karpathy@karpathy

Gemini Nano Banana Pro can solve exam questions *in* the exam page image. With doodles, diagrams, all that. ChatGPT thinks these solutions are all correct except Se_2P_2 should be "diselenium diphosphide" and a spelling mistake (should be "thiocyanic acid" not "thoicyanic") :O

English
933
2.5K
16.6K
2.5M
Seshu Adunuthula retweetledi
OpenAI
OpenAI@OpenAI·
Say hello to GPT-4o, our new flagship model which can reason across audio, vision, and text in real time: openai.com/index/hello-gp… Text and image input rolling out today in API and ChatGPT with voice and video in the coming weeks.
English
2.5K
12.5K
56K
22.8M
Seshu Adunuthula
Seshu Adunuthula@SeshuAd·
@AmazonHelp @amazon @ajassy My name is unique enough, so you should be able to look up my account. Some questions - Why is the item still showing up as next day delivery. - Why are you not resending the item if it got lost - Why are you not demoting the listing if the vendor selling the item is at fault.
English
2
0
0
22
Seshu Adunuthula
Seshu Adunuthula@SeshuAd·
This is my third time with @amazon package delivery. @ajassy , looks like they have even stopped trying. Do not want a refund, deliver the #$%&ing package
Seshu Adunuthula tweet media
English
1
0
0
65
Seshu Adunuthula retweetledi
Gwynne Shotwell
Gwynne Shotwell@Gwynne_Shotwell·
Happy birthday to @SpaceX! What a day! HUGE congratulations to the entire team for this incredible day: clean count (glad the shrimpers could get out in the nick of time!), liftoff, hot staging, Super Heavy boost back and coast (and likely a couple engines making mainstage during landing burn!), clean ship ”insertion” and coast, payload door cycling and prop transfer demo (to be confirmed!), and ship entry!
Gwynne Shotwell tweet media
English
615
2K
22.3K
1.6M
Seshu Adunuthula retweetledi
Andy Jassy
Andy Jassy@ajassy·
Already, more than 100,000 Amazon selling partners have used our GenAI listing tools to quickly and easily create high-quality product pages on Amazon.com. Now, we’re making it even easier with a new GenAI feature that lets sellers create Amazon listings for products they already sell on their website by just pasting in a link to the product’s page. Our GenAI will automatically turn it into optimized listing content for our store, saving sellers time and helping customers easily find products they’ll love. aboutamazon.com/news/innovatio…
English
39
48
383
124.1K
Seshu Adunuthula retweetledi
SpaceX
SpaceX@SpaceX·
Starship re-entering Earth's atmosphere. Views through the plasma
English
2.2K
16.5K
80.6K
14.2M
Seshu Adunuthula retweetledi
Bill Ackman
Bill Ackman@BillAckman·
Imagine the following: You're a man who serves as Chairman of the Board of a large University who led the search for the recently hired president. Your wife runs a non-profit in the DEI space. She is the only full-time employee of the organization, serving as Founder, CEO, and CFO. You serve as Treasurer. The non-profit ostensibly sells two principal products in the DEI space: 1. "Evidence-based 'how-to-guides' and 2. "The most comprehensive intersectional analytics platform of its kind..." but the non-profit has no revenues. It relies entirely on contributions to fund its operations, which principally consist of your wife's salary and some other ancillary overhead. There have been only two contributors to the non-profit, the University whose board you chair, which has contributed: 2018 $100,000 2019 $300,000 2020 $150,000 2021 $600,000 2022 $789,000 and a donor advised fund (DAF) affiliated with you which has contributed: 2018 $0 2019 $0 2020 $0 2021 $10,000 2022 $20,000 Doesn't this seem very strange? What if the University was @MIT? What if the Chairman was Mark Gorenberg? What if the non-profit is parity.org? Why are there so many conflicts/scandals concerning DEI organizations? All of the above can be found in MIT's and Parity.Org's IRS Form 990s which are available and summarized here: instrumentl.com/990-report/par…
English
1.9K
7.1K
32.8K
10.3M
Seshu Adunuthula retweetledi
Thomas Kurian
Thomas Kurian@ThomasOrTK·
Today, we’re announcing new capabilities across our AI stack, empowering organizations to build, use and successfully adopt generative AI to fuel their digital transformations. goo.gle/3ToiWLc
GIF
English
28
93
413
322.3K
Seshu Adunuthula retweetledi
Sundar Pichai
Sundar Pichai@sundarpichai·
Today developers can start building with our first version of Gemini Pro through Google AI Studio at ai.google.dev.  Developers have a free quota and access to a full range of features including function calling, embeddings, semantic retrieval, custom knowledge grounding, chat functionality and more. It supports 38 languages across 180+ countries. Gemini Ultra is coming early next year. We’re excited to see what you build! blog.google/technology/ai/…
Sundar Pichai tweet media
English
297
1K
5.8K
1.5M
Seshu Adunuthula retweetledi
Ethan Mollick
Ethan Mollick@emollick·
OMG, the AI Winter Break Hypothesis may actually be true? There was some idle speculation that GPT-4 might perform worse in December because it "learned" to do less work over the holidays. Here is a statistically significant test showing that this may be true. LLMs are weird.🎅
Rob Lynch@RobLynch99

@ChatGPTapp @OpenAI @tszzl @emollick @voooooogel Wild result. gpt-4-turbo over the API produces (statistically significant) shorter completions when it "thinks" its December vs. when it thinks its May (as determined by the date in the system prompt). I took the same exact prompt over the API (a code completion task asking to implement a machine learning task without libraries). I created two system prompts, one that told the API it was May and another that it was December and then compared the distributions. For the May system prompt, mean = 4298 For the December system prompt, mean = 4086 N = 477 completions in each sample from May and December t-test p < 2.28e-07 To reproduce this you can just vary the date number in the system message. Would love to see if this reproduces for others.

English
86
634
4.3K
1.4M
Seshu Adunuthula retweetledi
Jeff Dean
Jeff Dean@JeffDean·
. @zacharynado pointed out this stat we'd put in the white paper that in retrospect deserves calling attention to. During our Gemini Ultra training run, we had a goodput measure of 97% (goodput: the time spent computing useful new steps over the elapsed time of the training job). It's good to move forward almost all the time.
Zachary Nado@zacharynado

this program just proved yet again that Google has the best systems infra teams in the world, hands down, getting us an insane goodput of 97% for the Ultra training run

English
5
27
309
110.6K
Seshu Adunuthula retweetledi
Mihir Patel
Mihir Patel@mvpatel2000·
Gemini is so good. SO much better and SO much faster than GPT-4 🤯. I'm sold -- switching over
Mihir Patel tweet mediaMihir Patel tweet media
English
78
73
1.4K
686.5K
Seshu Adunuthula retweetledi
anton
anton@abacaj·
Damn they did it. Google shipped a stronger model
anton tweet media
English
180
223
3.8K
1.1M
Seshu Adunuthula retweetledi
@jason
@jason@Jason·
Yep, @google just leapfrogged @openai — game on!!! Think i am going to buy more Google stock — this is not investment advice.
English
295
480
4.9K
1.2M
Seshu Adunuthula retweetledi
Jeff Dean
Jeff Dean@JeffDean·
I’m very excited to share our work on Gemini today! Gemini is a family of multimodal models that demonstrate really strong capabilities across the image, audio, video, and text domains. Our most-capable model, Gemini Ultra, advances the state of the art in 30 of 32 benchmarks, including 10 of 12 popular text and reasoning benchmarks, 9 of 9 image understanding benchmarks, 6 of 6 video understanding benchmarks, and 5 of 5 speech recognition and speech translation benchmarks. Gemini Ultra is the first model to achieve human-expert performance on MMLU across 57 subjects with a score above 90%. It also achieves a new state-of-the-art score of 62.4% on the new MMMU multimodal reasoning benchmark, outperforming the previous best model by more than 5 percentage points. Gemini was built by an awesome team of people from @GoogleDeepMind, @GoogleResearch, and elsewhere at @Google, and is one of the largest science and engineering efforts we’ve ever undertaken. As one of the two overall technical leads of the Gemini effort, along with my colleague @OriolVinyalsML, I am incredibly proud of the whole team, and we’re so excited to be sharing our work with you today! There’s quite a lot of different material about Gemini available, starting with: Main blog post: blog.google/technology/ai/… 60-page technical report authored by th Gemini Team: deepmind.google/gemini/gemini_… In this thread, I’ll walk you through some of the highlights.
Jeff Dean tweet mediaJeff Dean tweet media
English
244
2.4K
12.6K
3.9M
Seshu Adunuthula retweetledi
Andy Jassy
Andy Jassy@ajassy·
Several years ago, when we started pursuing building our own chips, a lot of folks thought this was nuts. We heard a lot of the same refrains you often hear—why make this investment, why invest in a team and all the other fixed costs to develop your own chip when you can buy from other suppliers? And, while we knew we’d partner with those other companies for the foreseeable future, if your customers are telling you they’re thirsty for better price-performance, and you’re driven by what makes customers’ lives better and easier every day, you explore options to make it so. We realized pretty quickly that designing our own chips was going to be the best path to delivering this value for customers. We were lucky to find and join forces with the amazing Annapurna Labs team, who started with a chip (named Nitro) that offloaded security, networking, and some other virtualization functions from our servers so customers could use more of the server than they could before. Then, that team built a generalized CPU chip, Graviton, which has been very popular and impactful for customers, before embarking on building custom AI chips—Trainium (for training) and Inferentia (for inference)—which are also off to a strong start. Am very excited about our most recent chip releases at AWS re: Invent: Graviton4 and Trainium2. Graviton4 marks the fourth generation we’ve delivered in just five years (you can see the evolution from left to right in the image below), and it’s the most powerful and energy efficient multipurpose chip we have built to date. And with the surge of interest in generative AI, Trainium2 will help customers train their ML models faster, at a more advantaged price-performance. I’m really proud of the pace of innovation our teams are delivering on and what it is making possible for customers! aboutamazon.com/news/aws-reinv…
Andy Jassy tweet media
English
101
151
932
276.7K
Seshu Adunuthula retweetledi
The Foresight AI
The Foresight AI@TheForesightAI·
🚨 Google just launched Duet AI. It might overtake ChatGPT and Copilot. 7 features that you won’t believe are possible: [ Bookmark for later 🧵 ]
The Foresight AI tweet media
English
106
738
4.3K
1.5M
Seshu Adunuthula retweetledi
Ethan Mollick
Ethan Mollick@emollick·
LLMs are going to change retail. “GPT-4, here is a screenshot of Black Friday deals. Do research on them and tell me what you find. Are these good prices?” I didn’t see hallucinations (though i am sure they are possible) and the links all went directly to the right pages.
Ethan Mollick tweet mediaEthan Mollick tweet mediaEthan Mollick tweet media
English
45
176
1.3K
1.1M