Tootfinder

From #boingboing.net
“#Byte magazine ran in print from 1975 to 1998, a golden age that began with the first commercially successful personal computer and ending with the Digital Millennium Copyright Act (or the introduction of the iMac, perhaps.) At byte.tsundoku.io, you can explore the visual histo…

Is my host fast yet? is a web host TTFB (Time to First Byte) leaderboard: https://ismyhostfastyet.com/?client=mobile

TIL that the Xilinx PCIe endpoint IP, at least on some Versals (I assume it's likely the same on other parts but I've never looked) has a cursed non-compliant AXI4-Stream interface that uses TKEEP as a *dword* level valid strobe, rather than byte level as the spec requires.
Lovely.
The more I see of Xilinx IP blocks the more my decision to avoid then seems like the right one.

I've a "old #astronomy software" side project and I'm looking for the early Mac software "StarMap" or "Star Map" from Bruce Webster.
So far my searches came up empty, but I'm not a specialist in old Mac software.
Does anyone have a copy of this app?
It's described in detail in a July 1985 BYTE article: #retrocomputing

A little byte swap here, a change to CONFIG_LOGO_LINUX_VGA16 there, badabing badaboom - the framebuffer console has the right colors!
Linux assumes framebuffers to be little endian.
In case they are not, as I recall reading, the client is supposed to take care of conversion.
But what if the client is the (Linux internal) console driver?
I couldn't find a config option, so I hacked a byte swap into the color map helper (there are many similarly named functions btw):

Hybrid Tokenization Strategy for DNA Language Model using Byte Pair Encoding and K-MER Methods
Ganesh Sapkota, Md Hasibur Rahman
https://arxiv.org/abs/2507.18570 https://…

Hybrid Tokenization Strategy for DNA Language Model using Byte Pair Encoding and K-MER Methods
This paper presents a novel hybrid tokenization strategy that enhances the performance of DNA Language Models (DLMs) by combining 6-mer tokenization with Byte Pair Encoding (BPE-600). Traditional k-mer tokenization is effective at capturing local DNA sequence structures but often faces challenges, including uneven token distribution and a limited understanding of global sequence context. To address these limitations, we propose merging unique 6mer tokens with optimally selected BPE tokens gener…

The Art of Hide and Seek: Making Pickle-Based Model Supply Chain Poisoning Stealthy Again
Tong Liu, Guozhu Meng, Peng Zhou, Zizhuang Deng, Shuaiyin Yao, Kai Chen
https://arxiv.org/abs/2508.19774

The Art of Hide and Seek: Making Pickle-Based Model Supply Chain Poisoning Stealthy Again
Pickle deserialization vulnerabilities have persisted throughout Python's history, remaining widely recognized yet unresolved. Due to its ability to transparently save and restore complex objects into byte streams, many AI/ML frameworks continue to adopt pickle as the model serialization protocol despite its inherent risks. As the open-source model ecosystem grows, model-sharing platforms such as Hugging Face have attracted massive participation, significantly amplifying the real-world risks of…

What I really like about Rust is how much it feels like the code is practically writing itself thanks to all the excellent crates out there.
Once again, I am making great use of the zerocopy crate, specifically Ref:
https://docs.rs/zerocopy/latest/zerocopy/struct.Ref.html

"The [Tesla] owners are demanding that their lease contracts be terminated and reimbursed for the accrued legal costs."
☑️ Tesla Drivers Sue Elon Musk for Turning Their Cars Into "Extreme" Right-Wing Symbols
https://futurism.com/the-byte/tesla-dr

Tesla Drivers Sue Elon Musk for Turning Their Cars Into "Extreme" Right-Wing Symbols
Tesla drivers in France are suing Elon Musk's EV maker for turning their vehicles into what they characterize as "extreme-right" symbols.

While NUL and NULL both refer to numeric values 0, NUL is used in the context of ASCII (a single byte), whereas NULL is used in the context of pointers.
My headcanon is now that NULL is short for "NUL, Long".

Entropy-Driven Pre-Tokenization for Byte-Pair Encoding
Yifan Hu, Frank Liang, Dachuan Zhao, Jonathan Geuter, Varshini Reddy, Craig W. Schmidt, Chris Tanner
https://arxiv.org/abs/2506.15889

Entropy-Driven Pre-Tokenization for Byte-Pair Encoding
Byte-Pair Encoding (BPE) has become a widely adopted subword tokenization method in modern language models due to its simplicity and strong empirical performance across downstream tasks. However, applying BPE to unsegmented languages such as Chinese presents significant challenges, as its frequency-driven merge operation is agnostic to linguistic boundaries. To address this, we propose two entropy-informed pre-tokenization strategies that guide BPE segmentation using unsupervised information-th…

From Block to Byte: Transforming PCIe SSDs with CXL Memory Protocol and Instruction Annotation
Miryeong Kwon, Donghyun Gouk, Junhyeok Jang, Jinwoo Baek, Hyunwoo You, Sangyoon Ji, Hongjoo Jung, Junseok Moon, Seungkwan Kang, Seungjun Lee, Myoungsoo Jung
https://arxiv.org/abs/2506.15613

From Block to Byte: Transforming PCIe SSDs with CXL Memory Protocol and Instruction Annotation
This paper explores how Compute Express Link (CXL) can transform PCIe-based block storage into a scalable, byte-addressable working memory. We address the challenges of adapting block storage to CXL's memory-centric model by emphasizing cacheability as a key enabler and advocating for Type 3 endpoint devices, referred to as CXL-SSDs. To validate our approach, we prototype a CXL-SSD on a custom FPGA platform and propose annotation mechanisms, Determinism and Bufferability, to enhance performance…

Inside the Box: Everything I Did With an #Arduino Starter Kit
https://lopespm.com/hardware/2025/07/15/arduino.html

BGM-HAN: A Hierarchical Attention Network for Accurate and Fair Decision Assessment on Semi-Structured Profiles
Junhua Liu, Roy Ka-Wei Lee, Kwan Hui Lim
https://arxiv.org/abs/2507.17472

BGM-HAN: A Hierarchical Attention Network for Accurate and Fair Decision Assessment on Semi-Structured Profiles
Human decision-making in high-stakes domains often relies on expertise and heuristics, but is vulnerable to hard-to-detect cognitive biases that threaten fairness and long-term outcomes. This work presents a novel approach to enhancing complex decision-making workflows through the integration of hierarchical learning alongside various enhancements. Focusing on university admissions as a representative high-stakes domain, we propose BGM-HAN, an enhanced Byte-Pair Encoded, Gated Multi-head Hierar…

Is somebody aware of something like an “all time index” over all BYTE magazine issues? I'm specifically searching for BYTE articles on DTP (desktop publishing). The magazines itself are available via @… (mostly complete) but I don't want to manually walk through every single issues table of contents.

Floating-Point Data Transformation for Lossless Compression
Samirasadat Jamalidinan, Kazem Cheshmi
https://arxiv.org/abs/2506.18062 https://

Floating-Point Data Transformation for Lossless Compression
Floating-point data is widely used across various domains. Depending on the required precision, each floating-point value can occupy several bytes. Lossless storage of this information is crucial due to its critical accuracy, as seen in applications such as medical imaging and language model weights. In these cases, data size is often significant, making lossless compression essential. Previous approaches either treat this data as raw byte streams for compression or fail to leverage all pattern…

An was entdeckt Mensch, dass der anscheinende IT Fachartikel nur plumpes Marketing ist? Soll ich für euch dies mal Bit für Bit durchgehen oder nur ein Kyber Byte da lassen? 🙄😅🤷‍♂️
/s
»[…] Auffallend beim neuesten Mainframe-Modell der Z-Reihe von IBM ist aber das: Er verschlüsselt alle Daten in Echtzeit. Alle bedeutet in diesem Fall tatsächlich jedes einzelne Bit.«
#ibm

BYTE editors are people who separate the wheat from the chaff, and then
carefully print the chaff.

from my link log —
A Mind Is Born: 256 byte Commodore 64 demo.
https://linusakesson.net/scene/a-mind-is-born/
saved 2021-03-19 ht…

@… irgendwie geht bei Heise gerade im Safari auf macOS die Buchung von Abos nicht. Es gibt immer ein Download einer 0 Byte großen Datei ... Passiert auch im Safari iOS wenn ich mich nur versuche anzumelden.

It seems to me that MCP is a modern, cross-platform corollary to the Mac ecosystem’s AppleScript dictionaries. It's a great standard for discovering API endpoints and calling them in a standard way. (And as a bonus, it doesn't involve keeping track of four-byte codes.)
Because it's associated with the AI buzz, lots of developers are integrating it. But it's not limited to and doesn't have to be used with AI; there's a great opportunity to make it easy for humans…

AWS deleted my 10-year account and all data without warning
"On July 23, 2025, AWS deleted my 10-year-old account and every byte of data I had stored with them. No warning. No grace period. No recovery options. Just complete digital annihilation".
https://www.seuros.com/blog/aws…

"The RDBMS field is so young, we can actually see it grow through the pages of computer magazines of the 1980s. BYTE Magazine had its first issue dedicated to databases in November 1981, and then another one in October 1984. Dr. Dobb’s Journal did not feature an article about databases until 1984 and did not have many more throughout the decade; actually most of them were authored by Gene Head, and talk about dBASE."

BEAST: Efficient Tokenization of B-Splines Encoded Action Sequences for Imitation Learning
Hongyi Zhou, Weiran Liao, Xi Huang, Yucheng Tang, Fabian Otto, Xiaogang Jia, Xinkai Jiang, Simon Hilber, Ge Li, Qian Wang, \"Omer Erdin\c{c} Ya\u{g}murlu, Nils Blank, Moritz Reuss, Rudolf Lioutikov
https://arxiv.org/abs/2506.06072

BEAST: Efficient Tokenization of B-Splines Encoded Action Sequences for Imitation Learning
We present the B-spline Encoded Action Sequence Tokenizer (BEAST), a novel action tokenizer that encodes action sequences into compact discrete or continuous tokens using B-splines. In contrast to existing action tokenizers based on vector quantization or byte pair encoding, BEAST requires no separate tokenizer training and consistently produces tokens of uniform length, enabling fast action sequence generation via parallel decoding. Leveraging our B-spline formulation, BEAST inherently ensures…

ByteGen: A Tokenizer-Free Generative Model for Orderbook Events in Byte Space
Yang Li, Zhi Chen
https://arxiv.org/abs/2508.02247 https://arxiv.org/pdf/2508…

ByteGen: A Tokenizer-Free Generative Model for Orderbook Events in Byte Space
Generative modeling of high-frequency limit order book (LOB) dynamics is a critical yet unsolved challenge in quantitative finance, essential for robust market simulation and strategy backtesting. Existing approaches are often constrained by simplifying stochastic assumptions or, in the case of modern deep learning models like Transformers, rely on tokenization schemes that affect the high-precision, numerical nature of financial data through discretization and binning. To address these limitat…

Supernova: Achieving More with Less in Transformer Architectures
Andrei-Valentin Tanase, Elena Pelican
https://arxiv.org/abs/2507.15773 https://

Supernova: Achieving More with Less in Transformer Architectures
We present Supernova, a 650M-parameter decoder-only transformer that demonstrates how careful architectural design and tokenization innovation can achieve the performance of larger models while maintaining computational efficiency. Our architecture combines Rotary Positional Embeddings (RoPE), Grouped Query Attention (GQA) with a 3:1 compression ratio, RMSNorm for computational efficiency, and SwiGLU activation functions. A critical innovation is our custom 128,000-vocabulary byte-level BPE tok…

from my link log —
Histogramming bytes with positional popcount, GF2P8AFFINEQB edition.
http://bitmath.blogspot.com/2024/11/histogramming-bytes-with-positional.html
saved 2024-11-10

Histogramming bytes with positional popcount (GF2P8AFFINEQB edition)
A while ago, after some back and forth on twitter/X with @corsix , I dropped some implementation of byte histogramming without explaini...

OpenCXD: An Open Real-Device-Guided Hybrid Evaluation Framework for CXL-SSDs
Hyunsun Chung, Junhyeok Park, Taewan Noh, Seonghoon Ahn, Kihwan Kim, Ming Zhao, Youngjae Kim
https://arxiv.org/abs/2508.11477

OpenCXD: An Open Real-Device-Guided Hybrid Evaluation Framework for CXL-SSDs
The advent of Compute Express Link (CXL) enables SSDs to participate in the memory hierarchy as large-capacity, byte-addressable memory devices. These CXL-enabled SSDs (CXL-SSDs) offer a promising new tier between DRAM and traditional storage, combining NAND flash density with memory-like access semantics. However, evaluating the performance of CXL-SSDs remains difficult due to the lack of hardware that natively supports the CXL.mem protocol on SSDs. As a result, most prior work relies on hybri…

Dear Fediverse! Being German, I'm quite familiar with German computer magazines. But not with the UK and US world. What were the “professional level” computer magazines in ca. 1980-2010 which wrote about enterprise IT, Unix, supercomputers, hardware? I'm NOT (yet) interested in software engineering or programming languages and also not very much in Linux.
I already know BYTE magazine, Unix Review and several 8bit related magazines. What else?

Replaced article(s) found for q-fin.TR. https://arxiv.org/list/q-fin.TR/new
[1/1]:
- ByteGen: A Tokenizer-Free Generative Model for Orderbook Events in Byte Space
Yang Li, Zhi Chen

Tokens with Meaning: A Hybrid Tokenization Approach for NLP
M. Ali Bayram, Ali Arda Fincan, Ahmet Semih G\"um\"u\c{s}, Sercan Karaka\c{s}, Banu Diri, Sava\c{s} Y{\i}ld{\i}r{\i}m, Demircan \c{C}elik
https://arxiv.org/abs/2508.14292

Tokens with Meaning: A Hybrid Tokenization Approach for NLP
Tokenization plays a pivotal role in natural language processing (NLP), shaping how text is segmented and interpreted by language models. While subword methods such as Byte Pair Encoding (BPE) and WordPiece have been effective, they often struggle with morphologically rich and agglutinative languages because they rely on frequency rather than linguistic structure. We introduce a hybrid tokenization framework that combines rule-based morphological analysis with statistical subword segmentation. …

from my link log —
Alan Kay did not invent object-oriented programming.
https://www.hillelwayne.com/post/alan-kay/
saved 2025-05-11 https://

From Bytes to Ideas: Language Modeling with Autoregressive U-Nets
Mathurin Videau, Badr Youbi Idrissi, Alessandro Leite, Marc Schoenauer, Olivier Teytaud, David Lopez-Paz
https://arxiv.org/abs/2506.14761

From Bytes to Ideas: Language Modeling with Autoregressive U-Nets
Tokenization imposes a fixed granularity on the input text, freezing how a language model operates on data and how far in the future it predicts. Byte Pair Encoding (BPE) and similar schemes split text once, build a static vocabulary, and leave the model stuck with that choice. We relax this rigidity by introducing an autoregressive U-Net that learns to embed its own tokens as it trains. The network reads raw bytes, pools them into words, then pairs of words, then up to 4 words, giving it a mul…

Dynamic Chunking for End-to-End Hierarchical Sequence Modeling
Sukjun Hwang, Brandon Wang, Albert Gu
https://arxiv.org/abs/2507.07955 https://arxiv.org/pdf/2507.07955 https://arxiv.org/html/2507.07955
arXiv:2507.07955v1 Announce Type: new
Abstract: Despite incredible progress in language models (LMs) in recent years, largely resulting from moving away from specialized models designed for specific tasks to general models based on powerful architectures (e.g. the Transformer) that learn everything from raw data, pre-processing steps such as tokenization remain a barrier to true end-to-end foundation models. We introduce a collection of new techniques that enable a dynamic chunking mechanism which automatically learns content -- and context -- dependent segmentation strategies learned jointly with the rest of the model. Incorporating this into an explicit hierarchical network (H-Net) allows replacing the (implicitly hierarchical) tokenization-LM-detokenization pipeline with a single model learned fully end-to-end. When compute- and data- matched, an H-Net with one stage of hierarchy operating at the byte level outperforms a strong Transformer language model operating over BPE tokens. Iterating the hierarchy to multiple stages further increases its performance by modeling multiple levels of abstraction, demonstrating significantly better scaling with data and matching a token-based Transformer of twice its size. H-Nets pretrained on English show significantly increased character-level robustness, and qualitatively learn meaningful data-dependent chunking strategies without any heuristics or explicit supervision. Finally, the H-Net's improvement over tokenized pipelines is further increased in languages and modalities with weaker tokenization heuristics, such as Chinese and code, or DNA sequences (nearly 4x improvement in data efficiency over baselines), showing the potential of true end-to-end models that learn and scale better from unprocessed data.
toXiv_bot_toot

Exploiting Control-flow Enforcement Technology for Sound and Precise Static Binary Disassembly
Brian Zhao, Yiwei Yang, Yusheng Zheng, Andi Quinn
https://arxiv.org/abs/2506.09426

Exploiting Control-flow Enforcement Technology for Sound and Precise Static Binary Disassembly
Rewriting x86_64 binaries-whether for security hardening, dynamic instrumentation, or performance profiling is notoriously difficult due to variable-length instructions, interleaved code and data, and indirect jumps to arbitrary byte offsets. Existing solutions (e.g., "superset disassembly") ensure soundness but incur significant overhead and produce large rewritten binaries, especially for on-the-fly instrumentation. This paper addresses these challenges by introducing the Time Variance Author…

Replaced article(s) found for q-fin.CP. https://arxiv.org/list/q-fin.CP/new
[1/1]:
- ByteGen: A Tokenizer-Free Generative Model for Orderbook Events in Byte Space
Yang Li, Zhi Chen

H-Net : Hierarchical Dynamic Chunking for Tokenizer-Free Language Modelling in Morphologically-Rich Languages
Mehrdad Zakershahrak, Samira Ghodratnama
https://arxiv.org/abs/2508.05628

H-Net++: Hierarchical Dynamic Chunking for Tokenizer-Free Language Modelling in Morphologically-Rich Languages
Byte-level language models eliminate fragile tokenizers but face computational challenges in morphologically-rich languages (MRLs), where words span many bytes. We propose H-NET++, a hierarchical dynamic-chunking model that learns linguistically-informed segmentation through end-to-end training. Key innovations include: (1) a lightweight Transformer context-mixer (1.9M parameters) for cross-chunk attention, (2) a two-level latent hyper-prior for document-level consistency, (3) specialized handl…

Towards Memory Specialization: A Case for Long-Term and Short-Term RAM
Peijing Li, Muhammad Shahir Abdurraman, Rachel Cleaveland, Sergey Legtchenko, Philip Levis, Ioan Stefanovici, Thierry Tambe, David Tennenhouse, Caroline Trippel
https://arxiv.org/abs/2508.02992

Towards Memory Specialization: A Case for Long-Term and Short-Term RAM
Both SRAM and DRAM have stopped scaling: there is no technical roadmap to reduce their cost (per byte/GB). As a result, memory now dominates system cost. This paper argues for a paradigm shift from today's simple memory hierarchy toward specialized memory architectures that exploit application-specific access patterns. Rather than relying solely on traditional off-chip DRAM and on-chip SRAM, we envisage memory systems equipped with additional types of memory whose performance trade-offs benefit…