Room Mining

Welcome to @RoomMining we focus on stabilizing blockchain mining operations, providing solutions for distributed networks. #blockchain #mining #managment #btc

[Room Mining @RoomMining]

Mining ⛏ SHA-256 cryptocurrencies becomes stable at large enough level of scale, as the cost to attack the Proof of Work network (PoW 51% attack) becomes too expensive and unrealistic. This is why #Bitcoin  remains a stable network 10 years later. ⚡️ #btc

[NSA Cyber @NSACyber]

Effective Immediately, all organizations using PHP for their systems are advised to be prepared for an update addressing two critical vulnerabilities. PHP is widely used for web applications. These vulnerabilities often provide a direct path to the server's file system or database. If an immediate update is not feasible, it is recommend that organizations take the system offline until it can be fully mitigated. NSA will follow up shortly with more specific guidance.

[Room Mining @RoomMining]

@markgadala

[Rohit Ghumare @ghumare64]

Who's gonna tell vibe coders about...

1. SQL Injection
2. XSS
3. CSRF
4. CORS
5. SSRF
6. IDOR
7. Path Traversal
8. Mass Assignment
9. Clickjacking
10. Content Security Policy
11. Security Headers
12. Input Validation
13. Server-Side Authorization
14. Row-Level Security
15. Least Privilege
16. RBAC
17. Secrets Management
18. .env in .gitignore
19. API Key Rotation
20. Secret Scanning
21. Hashing vs Encryption
22. Password Salting
23. bcrypt & Argon2
24. JWT Expiry
25. Refresh Tokens
26. OAuth 2.0
27. OpenID Connect
28. Session Fixation
29. MFA
30. Brute Force Protection
31. Account Enumeration
32. Timing Attacks
33. File Upload Validation
34. Webhook Signature Verification
35. TLS Certificate Expiry
36. HSTS
37. Encryption at Rest
38. Dependency Vulnerabilities
39. Supply Chain Attacks
40. Threat Modeling
41. Indexes
42. EXPLAIN ANALYZE
43. N+1 Queries
44. Full Table Scans
45. Connection Pooling
46. Database Migrations
47. Down Migrations
48. Transactions
49. ACID
50. Isolation Levels
51. Deadlocks
52. Optimistic Locking
53. Pessimistic Locking
54. Normalization
55. Denormalization
56. Foreign Keys
57. Unique Constraints
58. Cascading Deletes
59. Soft Deletes
60. UUIDs vs Auto-Increment
61. Cursor-Based Pagination
62. Full-Text Search
63. Read Replicas
64. Replication Lag
65. Sharding
66. Partitioning
67. Hot Partitions
68. Postgres VACUUM
69. Materialized Views
70. Backups
71. Testing Your Restores
72. Point-in-Time Recovery
73. Change Data Capture
74. Outbox Pattern
75. ORM Lazy Loading
76. CAP Theorem
77. Eventual Consistency
78. Strong Consistency
79. Raft Consensus
80. Leader Election
81. Split Brain
82. Quorums
83. Clock Skew
84. Distributed Locks
85. Consistent Hashing
86. Bloom Filters
87. Two-Phase Commit
88. CQRS
89. Event Sourcing
90. Race Conditions
91. Backpressure
92. Load Shedding
93. Bulkheads
94. Jitter
95. Retry Storms
96. Cascading Failures
97. Thundering Herd
98. Cache Invalidation
99. Cache Hit Ratio
100. TTLs
101. Cache Warming
102. Write-Through vs Write-Back
103. Redis Eviction Policies
104. CDNs
105. Cache-Control Headers
106. ETags
107. Dead Letter Queues
108. Poison Messages
109. At-Least-Once Delivery
110. Exactly-Once Semantics
111. Message Ordering
112. Kafka Consumer Groups
113. Partition Keys
114. Background Jobs
115. Webhook Retries
116. DNS
117. DNS Propagation
118. HTTP Status Codes
119. HTTP Method Semantics
120. Keep-Alive
121. HTTP/2
122. WebSockets
123. Server-Sent Events
124. Long Polling
125. gRPC
126. Protocol Buffers
127. API Versioning
128. OpenAPI Specs
129. Backward Compatibility
130. Request Size Limits
131. Compression
132. Latency vs Throughput
133. Egress Fees
134. VPCs
135. Subnets
136. NAT Gateways
137. Firewalls
138. Security Groups
139. Service Mesh
140. Ingress Controllers
141. Health Checks
142. Liveness vs Readiness Probes
143. Graceful Shutdown
144. Connection Draining
145. Stateless Services
146. Failover
147. Multi-Region
148. Availability Zones
149. Single Points of Failure
150. Disaster Recovery
151. RTO & RPO
152. SLAs
153. SLOs
154. Error Budgets
155. Incident Response
156. On-Call
157. Runbooks
158. Postmortems
159. Chaos Engineering
160. Graceful Degradation
161. Autoscaling
162. Horizontal vs Vertical Scaling
163. Cold Starts
164. Capacity Planning
165. Load Testing
166. Memory Leaks
167. OOM Killer
168. Structured Logging
169. Log Levels
170. Log Rotation
171. Distributed Tracing
172. OpenTelemetry
173. Correlation IDs
174. Metrics Cardinality
175. p99 Latency
176. Alert Fatigue
177. Error Tracking
178. Profiling
179. Flame Graphs
180. Infrastructure as Code
181. Terraform State
182. GitOps
183. Blue-Green Deployments
184. Canary Releases
185. Rollbacks
186. Feature Flags
187. Environment Parity
188. Staging Environments
189. 12-Factor Apps
190. Multi-Stage Builds
191. Non-Root Containers
192. Image Scanning
193. Resource Requests & Limits
194. Pod Disruption Budgets
195. Semantic Versioning
196. Lockfiles
197. Reproducible Builds
198. Branch Protection

[Ben Cera @Bencera]

never join a startup if the founder isn't slightly delusional

[vitalik.eth @VitalikButerin]

The cryptographic world computer:

https://t.co/LF2JGU38Rx

My attempt to express in somewhat concise terms the true meaning of basically everything planned to happen to Ethereum starting from the fork after Hegota. It's really not just a blockchain anymore. It's a hybrid architecture that combines together blockchains and modern cryptography, to enable much more powerful properties.

FOCIL, EIP-8288, Lean consensus, state management, formal verification, advanced mempool improvements (including privacy), and the longer-term specter of obfuscation all mentioned.

[vitalik.eth @VitalikButerin]

qwen3.8-flash-next
ethereum client
100+ GB of local downloaded wikipedia + gutenberg + science articles
what else?

(Getting rid of the need for centralized pinning services in IPFS is definitely high up the prio list)

[Superman @thesupermannx]

Nvidia has lost it 🤯

China open-sourced an AI that writes CUDA better than humans experts.

For years, writing high-performance GPU kernels has been the ultimate dark art in tech.

It requires brutal, low-level hardware expertise.. managing memory hierarchies, cache lines, and parallel thread blocks manually. Even top-tier frontier models like Claude and Gemini have historically choked on it, consistently losing to automated compilers like PyTorch.

Then ByteDance Seed and Tsinghua University dropped a paper.

They built a system called CUDA Agent.

Instead of treating code generation as a simple text prompt, they built a large-scale agentic reinforcement learning system.

They dropped the AI into a real, sandboxed CUDA development environment complete with automated execution, profiling, and hardware verification tools.

The AI was forced to iteratively write code, compile it, run it on physical GPUs, check for errors, and optimize its own execution speed.

Over and over again.

The results completely shatter current limits.

Tested on KernelBench, CUDA Agent didn't just match human engineers. It outperformed the strongest proprietary Western models by roughly 40% on the hardest benchmarks.

On complex multi-operator models, it ran up to 92% to 100% faster than traditional compiler optimization (torch.compile).

It discovered custom memory access patterns, advanced tiling strategies, and kernel fusions that static compilers couldn't see.

For over a decade, human engineers held a monopoly on optimizing hardware performance.

That monopoly just ended.

[brantly @BrantlyMillegan]

🤯 it's happening guys... @OpenRouter (just acquired by @Stripe) offers *Sign in with Ethereum* alongside Google and Github @signinethereum

[elvis @omarsar0]

Super interesting new work from NVIDIA.

(bookmark it)

They suggest building agents as Python objects.

Very cool idea and I think it could a lot with agent reliability.

More below:

Agent development today spreads across prompt templates, tool schemas, callback code, and workflow graphs. NOOA replaces all four with one abstraction.

An agent is a Python object. Its methods are the actions the model can take, its fields hold state, its docstrings are the prompts, and its type annotations act as contracts.

A method whose body is "..." gets completed at runtime by a validated LLM loop. A method with a normal body stays deterministic Python.

That single convention puts the boundary between probabilistic and deterministic behavior right in the source.

Agent behavior becomes testable, traceable, and refactorable with the same tools you already use on the rest of your codebase.

NVIDIA reports six model-facing ideas combined on one surface, including pass-by-reference over live objects and model-callable harness APIs for context and events, evaluated on SWE-bench Verified, Terminal-Bench 2.0, and ARC-AGI-3.

Paper: https://t.co/PCtFtVY8rT

Learn to build effective AI agents in our academy: https://t.co/1e8RZKs4uX

[Devcon 8 | Mumbai, India 🇮🇳 @EFDevcon]

11 years of building, experimenting, questioning and imagining what the internet could become.

Ethereum’s future is still being shaped by its community.

To celebrate @ethereum's birthday, take 11% off Devcon 8 GA tickets through August 11.

[Room Mining @RoomMining]

@isabelle_zhou @OpenAI ⚡️

[0xMarioNawfal @RoundtableSpace]

The Hugging bay, The Pirate bay for open LLM's, model weights downloadable with torrents.

This is a game changer.

https://t.co/nuZQ68aluH

[Room Mining @RoomMining]

@boardyai We offer blockchain mining and management services ⚡️

[Tech with Mak @techNmak]

A dev got so frustrated watching his AI agent write 500 lines for a 5-line problem that he built a fix.

He called it Ponytail. Named after the guy every team has - long ponytail, oval glasses, been there longer than the version control. You show him fifty lines; he looks at them, says nothing, and replaces them with one.

Now your agent does the same. Before writing anything, it looks for a reason not to.

80-94% less code. 47-77% cheaper. 3-6x faster.

The best code is the code you never wrote.

GitHub Repo: https://t.co/WnFp9YNY53

[Rony @Ronycoder]

Instead of watching an hour of Netflix, watch this 30-minute speech by the Head of Anthropic’s Coding Agents research team. It will teach you more about vibe coding than 100 paid courses.

[sarpstar @sarpstar]

Viktor X'te tasarım tarafında takip ettiğim tartışmasız en iyi isimlerden biri.

Adamın çıkardığı işler her seferinde estetikten yıkılıyor.

Ve şimdi Claude Design + Opus 4.7 üzerine 18 dakikalık tutorial çıkarmış.

Kendi adıma bu videoyu izledikten sonra tasarımlarınızın tamamen bambaşka bir seviyeye çıkacağına eminim.

Claude Design zaten tek başına oyunu değiştiriyor, bir de Viktor gibi birinin elinden öğrenmek varken kaçırılmayacak bir kaynak.

Yumulun!

[Resolv @resolvfinance]

Here’s to the crazy ones.

[Room Mining @RoomMining]

@ethereum @zkPass 🔥

[Ethereum @ethereum]

ZKPass is built on Ethereum.

@zkPass is a privacy-preserving identity protocol letting users prove information about themselves without revealing the underlying data.

It enables secure verification of credentials onchain while keeping personal information private by default.