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Didgeridoo playing as alternative treatment for obstructive sleep apnoea syndrome: randomised controlled trial

Didgeridoo playing as alternative treatment for obstructive sleep apnoea syndrome: randomised controlled trial

✨ Read this trending post from Hacker News πŸ“– πŸ“‚ **Category**: πŸ’‘ **What You’ll Learn**: Abstract Objective To assess the effects of didgeridoo playing on daytime sleepiness and other outcomes related to sleep by reducing collapsibility of the upper airways in patients with moderate obstructive sleep apnoea syndrome and snoring. Design Randomised controlled trial. Setting Private practice of a didgeridoo instructor and a single centre for sleep medicine. Participants 25 patients aged > 18 years with an apnoea-hypopnoea index between 15 and 30 and who complained about snoring. Interventions Didgeridoo lessons and daily practice at home with standardised instruments for…
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White Rabbit

White Rabbit

πŸ’₯ Explore this must-read post from Hacker News πŸ“– πŸ“‚ **Category**: πŸ“Œ **What You’ll Learn**: White Rabbit provides sub-nanosecond accuracy and picoseconds precision of synchronization for large distributed systems. It also allows for deterministic and reliable data delivery.White Rabbit allows you to precision time-tag measured data and lets you trigger data taking in large installations while at the same time using the same network to transmit data.sub-nanosecond synchronizationconnecting thousands of nodestypical distances of 10 km between nodesEthernet-based gigabit rate reliable data transferfully open hardware, firmware and softwaremulti-vendor commercially produced hardwareContactMaciej LipinskiTagsDocumentation White Rabbit πŸ”₯ **What’s your take?** Share your thoughts…
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Jira IS Turing-Complete

Jira IS Turing-Complete

πŸ”₯ Discover this awesome post from Hacker News πŸ“– πŸ“‚ **Category**: πŸ’‘ **What You’ll Learn**: Jira IS Turing-Complete Nicolas Seriot Computation > Jira is Turing-Complete Building a Minsky Machine in Atlassian Automation22nd May 2026 Engineering folklore holds that Jira (Atlassian's project-tracking tool) is Turing-complete. Existing claims point vaguely at automation features without exhibiting a reduction. This article supplies a proof, with setup instructions and execution trace. Mapping the Computational Model A Minsky register machine needs only two unbounded counters and a finite set of labeled instructions: INC r; goto S DEC r; if r == 0 goto S else goto…
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Companies Are Just a Graph of Algorithms

Companies Are Just a Graph of Algorithms

✨ Explore this awesome post from Hacker News πŸ“– πŸ“‚ **Category**: πŸ“Œ **What You’ll Learn**: I think the reason so many people don't understand how big AI is going to be is that they don't understand that everything is an algorithm.Specifically, they don't realize that companies are just a collection of algorithms.What do I mean by that?Well, let's say that your company takes pictures, cleans them up, stylizes them, and adds a captionβ€”which customers can then download in a large format. Let's call the company Memories.The company started in the early 2000's, founded by an artist/photographer, and here's how it…
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What Matters in Practical Learned Image Compression

πŸ’₯ Explore this insightful post from Hacker News πŸ“– πŸ“‚ **Category**: πŸ“Œ **What You’ll Learn**: We introduce PICO (Perceptual Image Codec) β€” the first learned codec that is both practical, and optimized directly for the human visual system. To derive it, we perform a comprehensive study of modeling choices for practical learned codecs, and search over millions of model configurations to jointly optimize over perceptual quality and on-device runtime. Based on large-scale subjective user studies, PICO provides 2.3-3Γ— bitrate savings against AV1, AV2, VVC, ECM and JPEG-AI, and 20-40% bitrate savings against the best learned codec alternatives. At the same…
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Building Pi With Pi | Armin Ronacher’s Thoughts and Writings

Building Pi With Pi | Armin Ronacher’s Thoughts and Writings

πŸ’₯ Discover this awesome post from Hacker News πŸ“– πŸ“‚ **Category**: βœ… **What You’ll Learn**: written on May 24, 2026 Pi is now part of Earendil, but in the important sense it is still Mario’s project. He has been living with its issue tracker longer than I have, and he has been exposed to the weirdness of the new form of agent traffic in Open Source projects for longer too. This post is mostly a reflection of my own experience after spending more time in the tracker, using Pi to work on Pi, and watching what I have learned about…
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Page introuvable… | Usborne | Des livres pour explorer le monde

Page introuvable… | Usborne | Des livres pour explorer le monde

πŸš€ Discover this trending post from Hacker News πŸ“– πŸ“‚ **Category**: πŸ“Œ **What You’ll Learn**: Page introuvable... | Usborne | Des livres pour explorer le monde The store will not work correctly when cookies are disabled. JavaScript seems to be disabled in your browser. For the best experience on our site, be sure to turn on Javascript in your browser. chev_right_small instagram twitter tiktok threads plus alert_in_circle basket basket_full chev_down chev_right cir_eye cir_pencil cir_puzzle c_scissors cross pencil message linkedin linked youtube link look paypal p_discover p_maestro p_mastercard p_paypal p_visa search secure sq_book sq_earphones sq_eye…
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AI Chip Component Costs: Memory at 63% | Epoch AI

AI Chip Component Costs: Memory at 63% | Epoch AI

πŸ’₯ Read this insightful post from Hacker News πŸ“– πŸ“‚ **Category**: βœ… **What You’ll Learn**: For each AI chip designed by Nvidia, AMD, Google, and Amazon, we estimate the per-chip cost of four component categories: memory (HBM), logic dies, advanced packaging (CoWoS), and auxiliary components. We then multiply those per-chip costs by estimated quarterly production volumes to get total component spending in each category, and compute each category’s share of total component spending per quarter from Q1 2024 to Q4 2025. We find that memory’s share rose from 52% to 63% over this period, while packaging fell from 19% to…
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Don’t know where your data is from? Bayesian modeling for unknown coordinates

✨ Check out this insightful post from Hacker News πŸ“– πŸ“‚ **Category**: βœ… **What You’ll Learn**: location_surface_grids = πŸ”₯ with location_error_gp_model: for multiplier, X_noisy_value in zip(multipliers, noisy_xs): pm.set_data(πŸ’¬) posterior_mean_point = πŸ’¬ f_mean, _ = gp_location.predict(Xnew, point=posterior_mean_point, diag=True, pred_noise=False) location_surface_grids[multiplier] = f_mean.reshape(n_prediction_grid, n_prediction_grid) naive_kde_grids = πŸ’¬ kde_bandwidths = { multiplier: location_error_idatas[multiplier].posterior["β„“"].mean(("chain", "draw")).item() for multiplier in multipliers } for multiplier, X_noisy_value in zip(multipliers, noisy_xs): squared_distance = ( (Xnew[:, 0, None] - X_noisy_value[:, 0]) ** 2 + (Xnew[:, 1, None] - X_noisy_value[:, 1]) ** 2 ) weights = np.exp(-0.5 * squared_distance / kde_bandwidths[multiplier]**2) naive_kde_grids[multiplier] = (weights @ y_walker / weights.sum(axis=1)).reshape(n_prediction_grid, n_prediction_grid) location_norm =…
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Migrating from Go to Rust

πŸ’₯ Explore this trending post from Hacker News πŸ“– πŸ“‚ **Category**: βœ… **What You’ll Learn**: Out of all the migrations I help teams with, Go to Rust is a bit of an outlier. It’s not a question of β€œis Rust faster?” or β€œdoes Rust have types?”, Go already gets you most of the way there. The discussion is mostly about correctness guarantees, runtime tradeoffs, and developer ergonomics. A quick disclaimer before we start: this guide is heavily backend-focused. Backend services are where Go is strongest, small static binaries, a standard library focused on networking, and an ecosystem of libraries for…
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