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amund

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https://amund.blog

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github.com 1mo ago

Pi-Mojo – A Mojo Port of Pi AI Agent Toolkit

amund
1pts0
atsentia.com 6mo ago

6.5 GB/S JSON Parsing in Mojo – Beating Rust and C++ on Apple Silicon (M3 Ultra)

amund
4pts0
atsentia.com 7mo ago

Bits is all you need (and 3.6 bit what you have?) for resource-efficient LLMs?

amund
1pts0
atsentia.com 7mo ago

Towards milli-joules per token – AI on the Apple Watch

amund
1pts0
amund.blog 1y ago

Grokking Implementations in Jax/Flax and PyTorch

amund
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amundtveit.com 7y ago

Predicting Bitcoin Price with AutoML Tables

amund
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amundtveit.com 8y ago

Thoughts on AI replacing coders by 2040

amund
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corp.zedge.net 8y ago

Serverless Thrift APIs in Python on AWS Lambda

amund
2pts0
corp.zedge.net 8y ago

Hotswapping Core ML (Deep Learning) Models on the iPhone

amund
1pts0
amundtveit.com 9y ago

A Closer Look at Equity Crowd Funding

amund
1pts0
corp.zedge.net 9y ago

Creative AI on the iPhone: GAN with Apple's CoreML Tools

amund
2pts0
amundtveit.com 9y ago

Keras Deep Learning with Apple’s CoreMLTools on iOS 11

amund
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amundtveit.com 9y ago

Early Experiences with Deep Learning on a Laptop with Nvidia GTX 1070 GPU

amund
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amundtveit.com 9y ago

Unsupervised Deep Learning – ICLR 2017 Discoveries

amund
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amundtveit.com 9y ago

Autoencoders in Deep Learning – ICLR 2017 Discoveries

amund
2pts0
amundtveit.com 9y ago

Deep Learning with Reinforcement Learning – ICLR 2017 Discoveries

amund
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amundtveit.com 9y ago

Deep Learning with Generative Adverserial Networks – ICLR 2017 Discoveries

amund
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amundtveit.com 9y ago

Deep Learning for Natural Language Processing – ICLR 2017 Discoveries

amund
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corp.zedge.net 10y ago

Deep Learning for Mobile Personal Expression at Zedge

amund
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deeplearning.education 10y ago

Why Deep Learning matters

amund
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deeplearningkit.org 10y ago

Deep Learning for Text Summarization

amund
3pts0
deeplearningkit.org 10y ago

Deep Learning for Named Entity Recognition

amund
4pts0
www.youtube.com 10y ago

How to Get Started with Deep Learning Kit for TvOS on Apple TV

amund
1pts0
www.youtube.com 10y ago

How to Get Started with Deep Learning Kit for iOS

amund
1pts0
deeplearningkit.org 10y ago

DeepLearningKit – Open Source Deep Learning Framework for iOS, OS X and TvOS

amund
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memkite.com 10y ago

Memkite – Deep Learning for iOS (tested on iPhone 6S) in Metal and Swift

amund
4pts0
memkite.com 10y ago

Swift and Metal GPU Programming on TvOS for the New Apple TV

amund
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memkite.com 11y ago

Swift and Metal GPU Programming on OS X 10.11 / El Capitan

amund
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memkite.com 11y ago

Threadmill Desks – The Future Software Engineer Office Rig?

amund
3pts1
memkite.com 11y ago

Deeplearning.University – Bibliographies from Lisa Labs (Yoshua Bengio’s Lab)

amund
1pts0

Zedge | Data Scientist and Android SWE positions | Trondheim, Norway | ONSITE, FULL-TIME | EU/EEC work permit/visa required | https://corp.zedge.net/join-our-playground

Zedge (NYSE MKT: ZDGE) provides personalization apps/services (primarily on Android and iOS) for ~30 million monthly active users.

On the data science side we use Hadoop and (increasingly) Clickhouse for analytics in combination with both using and developing Deep Learning (Keras/Tensorflow) for content analysis (e.g. audio and images) and content discovery (e.g. recommender systems and search). We are looking for data scientist candidates that also have solid software engineering skills, a doer mindset and an aptitude to learn.

Blog posts related to some of the things we've been looking into related to Deep Learning:

- https://corp.zedge.net/developers-blog/creative-ai-on-the-ip...

- https://corp.zedge.net/developers-blog/deep-learning-at-zedg...

(I am leading the data science team)

Zedge | Trondheim, Norway and New York City, NY| Full Time/Onsite

Zedge (NYSE Market: ZDGE) is a content platform, and global leader in smartphone personalization, with more than 200 million app installs and 30 million monthly active users.

We are looking for: Android Developers - http://corp.zedge.net/join-our-playground#senior-android-dev... Backend Developers - http://corp.zedge.net/join-our-playground#senior-ios-develop... Data Scientists - http://corp.zedge.net/join-our-playground#senior-ios-develop... iOS Developers - http://corp.zedge.net/join-our-playground#senior-ios-develop...

More positions at: http://corp.zedge.net/join-our-playground (Our Early Tech Blog: http://corp.zedge.net/developers-blog)

Yes, I know the bibliography is a bit sparse right now, but we're gradually increasing its coverage. Will also add more annotations to it (per category), e.g. areas where deep learning could be applied but is lightly or not at all applied yet.

The Envisage Research Project - http://envisage-project.eu - is working on developing formal methods for software engineering for the cloud, ref: http://envisage-project.eu/wp-content/uploads/2013/10/Envisa... "ENVISAGE will create a development framework based on formal methods to include resources and resource management into the design phase in software engineering for the cloud. This will improve the competitiveness of SMEs and profoundly influence business ICT strategies in virtualized computing"

I'm probably not clear enough in the blog post: The intention is to use Twitter as a news source, i.e. crawl and index top URIs (which can be any type of news, blog and other content). The underlying idea is that URIs on tweets give a good sample of _all_ overall knowledge production per day.

There are also of course some benefits of having all the interaction happen between you and your device that I haven't talked about in the blog post, e.g. increased privacy (no data collection), lower latency (disk seek on a mobile or tablet SSD - 100 microseconds) - is roughly 1000 times lower than the latency of accessing 3G or 4G can be (up to hundreds of milliseconds)

Ran Raz proved that Matrix Inversion is O(n^2 lg n), ref: Ran Raz. On the Complexity of Matrix Product. SIAM Journal on Computing, 32(5):1356–1369, 2003.

Based on that I deduced that Matrix Multiplication is O(n^2 lg n), http://amundtveit.info/publications/2003/ComplexityOfMatrixI...

Regarding even faster operations, it has been hypothetized that all matrices are Toeplitz or Hankel (which have O(n lg n) algorithms), ref: D. S. Mackey, N. Mackey, and S. Petrovic. Is Every Matrix Similar to a Toeplitz Matrix. Linear Algebra & its Applications, 297:87­105, 1999. But that was proved to not be the case: T. Amdeberhan and G. Heinig - http://www-math.mit.edu/~tewodros/georgmemoriam.pdf

It is always a good time to join Google, and even more now when Larry Page is in charge. He is in the same league as Steve Jobs wrt being forward-looking, but less known due to lower public profile.

All companies with more than 1 person have or get issues - also Google - but the willingness and ability to measure and fix issues is probably much higher within Google than most sizable companies.

note: I am a xoogler and worked there for 4 years.

Sorry about that, have fixed that now - thanks for noticing (I was mainly focused on the names with 2 syllables). Regarding the rest of the analysis I believe the list of names with few syllables speaks for itself, and regarding the predictions it is of course in the same tradition as a monkey throwing darts, but with slightly more empirical support.

I've been using Wave for startup product collaboration (a development project with 2 people on one location and the 3rd person on another location). The way Wave has been used is roughly like a digital shared whiteboard for product ideas and requirements.

The reasons why I use Wave is because it works relatively good (except that it gets somewhat less responsive on very long threads) and that it needs zero maintenance from our side.

PG: How about creating a competition for making the best search for news.ycombinator.com?

Potential way it could be arranged: E.g. require that participants have their yc name as part of the user agent string while crawling and that they are allowed to maximum crawl 1000-10000 threads(with all comments) and create search for that. Or perhaps create a recent dataset with stories/threads so all participants have the same data.

Potential price for the winner: Serve search on news.ycombinator.com for one year?

thank, perhaps it was due to an unusual traffic spike for a small site and that the words malware, spam and botnets occur in paper titles on the page?