Secure yourself with 5 steps: 1. Use a modern HD wallet. Any current hardware or standard software wallet generates a fresh address per receive - that alone puts you in the safe column. 2. Never reuse an address you have spent from. Spending reveals the public key forever; anything left behind sits in the exposed pile. 3. If you hold coins on old or reused addresses, move them once to a freshly generated modern address. That single transaction takes them out of the harvest-now-decrypt-later pool. 4. Watch for the upgrade, not the headlines. The milestone that matters is a quantum-resistant address type going live (BIP-360 or a successor) - adopt it when it ships. Chip announcements with bigger qubit counts are not the signal. 5. Do not panic-sell on quantum news. The threat is a solvable, years-away engineering problem the ecosystem is already working on - a reason for hygiene, not for exit. full version with the tables at https://gmdmarkets.com/does-quantum-threaten-bitcoin submitted by /u/Prestigious-Bank2145 [link] [Kommentare]
Humans miss this subtle sound of danger approaching – but this cheap gadget can sound the mosquito alarm.
Is artificial intelligence displacing young workers at the start of their careers? Not so far. But that could change.
Learn to tailor your resume to a job description fast using a base resume and role workspaces. Cut a 45-minute chore down to under a minute.
Or why I think open-weights models aren't a threat to American Labs
Dreh am Rad, verpflichte fünf Legenden mit einem Budget von $100M und simuliere 82 Spiele. Finde heraus, wie oft dein Team die rekordträchtigen 73-9-Warriors schlagen würde. Kostenlos, ohne Anmeldung.
If you ask anybody in Toronto, they’ll tell you that raccoons, AKA the Procyon lotor (Latin for “before-dog washer,” given their apparent penchant for washing their food), are everywhere. The creat…
Hello, I recently finished reading this survey paper: Deep learning tackles single-cell analysis – A survey of deep learning for scRNA-seq analysis, which comprehensively covers 25 different methods across 6 subcategories for applying deep learning to scRNA-seq analysis. To summarize the methods from this paper, I prepared a table containing the Category, Method, Purpose, Architecture, Metrics, Explanation, and the specific Novelty of each method. I hope you find this summary useful. https://preview.redd.it/n3okgq66t1eh1.png?width=1662&format=png&auto=webp&s=fb71b306d3ffc346f243b04ccc9fe7a14076fbd7 https://preview.redd.it/njs5lq66t1eh1.png?width=1662&format=png&auto=webp&s=1dcdebbef3f2746b1e94f7182c9e4a11f10a7f12 https://preview.redd.it/zsv2yq66t1eh1.png?width=1662&format=png&auto=webp&s=05ecb58355b6a32a25d32cc25a2a9e500f9cd489 submitted by /u/teraRockstar [link] [Kommentare]