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731 个榜单

Barchart

全部
12天前更新
  • 011.2万
    CARR Put $53
    Put · 行权价 $53 · 到期 2026-10-02 · 量/OI：11540 · 成交量：11,540 · 未平仓：1 · 最新价：$0.5 · 隐波：0.3543%
  • 025953
    BTDR Call $14.5
    Call · 行权价 $14.5 · 到期 2026-09-18 · 量/OI：5953 · 成交量：5,953 · 未平仓：1 · 最新价：$0.21 · 隐波：1.0364%
  • 034212
    C Put $122
    Put · 行权价 $122 · 到期 2026-10-02 · 量/OI：4212 · 成交量：8,424 · 未平仓：2 · 最新价：$1.02 · 隐波：0.2943%
  • 042304
    BLFS Call $40
    Call · 行权价 $40 · 到期 2026-09-18 · 量/OI：2304 · 成交量：2,304 · 未平仓：1 · 最新价：$0.15 · 隐波：0.2408%
  • 051948
    UNIT Call $12
    Call · 行权价 $12 · 到期 2026-09-18 · 量/OI：1948.5 · 成交量：3,897 · 未平仓：2 · 最新价：$0.15 · 隐波：0.6236%
  • 061397
    BX Put $155
    Put · 行权价 $155 · 到期 2026-11-20 · 量/OI：1396.84 · 成交量：26,540 · 未平仓：19 · 最新价：$17 · 隐波：0.3659%
  • 071310
    MDLZ Put $64
    Put · 行权价 $64 · 到期 2026-09-11 · 量/OI：1310 · 成交量：1,310 · 未平仓：1 · 最新价：$1.59 · 隐波：0.2044%
  • 08867
    AG Call $28
    Call · 行权价 $28 · 到期 2026-09-04 · 量/OI：867 · 成交量：867 · 未平仓：1 · 最新价：$0.01 · 隐波：0.719%
  • 09810
    XPEV Put $12.5
    Put · 行权价 $12.5 · 到期 2026-09-18 · 量/OI：810 · 成交量：810 · 未平仓：1 · 最新价：$1.04 · 隐波：0.5053%
  • 10770
    ENVX Call $1
    Call · 行权价 $1 · 到期 2026-10-02 · 量/OI：770 · 成交量：770 · 未平仓：1 · 最新价：$2.39 · 隐波：2.675%
  • 11700
    IREN Put $37.5
    Put · 行权价 $37.5 · 到期 2026-09-11 · 量/OI：700.5 · 成交量：4,203 · 未平仓：6 · 最新价：$2.2 · 隐波：0.9923%
  • 12509
    AMKR Call $61
    Call · 行权价 $61 · 到期 2026-10-02 · 量/OI：509 · 成交量：1,527 · 未平仓：3 · 最新价：$0.76 · 隐波：0.6863%
  • 13489
    ANF Call $150
    Call · 行权价 $150 · 到期 2026-09-04 · 量/OI：489 · 成交量：489 · 未平仓：1 · 最新价：$5.4 · 隐波：0.7245%
  • 14485
    META Put $582.5
    Put · 行权价 $582.5 · 到期 2026-08-26 · 量/OI：484.75 · 成交量：9,695 · 未平仓：20 · 最新价：$7.45 · 隐波：0.2242%
  • 15472
    ON Put $74
    Put · 行权价 $74 · 到期 2026-09-25 · 量/OI：472 · 成交量：472 · 未平仓：1 · 最新价：$4.85 · 隐波：0.5258%
  • 16470
    DLTR Put $110
    Put · 行权价 $110 · 到期 2026-10-16 · 量/OI：470 · 成交量：470 · 未平仓：1 · 最新价：$1.52 · 隐波：0.474%
  • 17450
    PAAS Call $60
    Call · 行权价 $60 · 到期 2027-04-16 · 量/OI：450 · 成交量：900 · 未平仓：2 · 最新价：$6.8 · 隐波：0.5356%
  • 18421
    ANF Call $165
    Call · 行权价 $165 · 到期 2026-09-18 · 量/OI：421 · 成交量：421 · 未平仓：1 · 最新价：$3 · 隐波：0.5909%
  • 19396
    AXTI Call $32
    Call · 行权价 $32 · 到期 2026-09-04 · 量/OI：396 · 成交量：396 · 未平仓：1 · 最新价：$32.5 · 隐波：2.7642%
  • 20395
    BURL Put $315
    Put · 行权价 $315 · 到期 2026-09-11 · 量/OI：395 · 成交量：395 · 未平仓：1 · 最新价：$15.92 · 隐波：0.6043%
  • 21377
    AXTI Call $34
    Call · 行权价 $34 · 到期 2026-08-28 · 量/OI：377 · 成交量：377 · 未平仓：1 · 最新价：$30.75 · 隐波：5.3417%
  • 22352
    AXTI Call $31
    Call · 行权价 $31 · 到期 2026-09-04 · 量/OI：352 · 成交量：352 · 未平仓：1 · 最新价：$35.05 · 隐波：2.8741%
  • 23350
    GMAB Call $45
    Call · 行权价 $45 · 到期 2026-12-18 · 量/OI：350 · 成交量：1,750 · 未平仓：5 · 最新价：$0.99 · 隐波：0.4844%
  • 24329
    META Put $577.5
    Put · 行权价 $577.5 · 到期 2026-08-26 · 量/OI：328.63 · 成交量：15,774 · 未平仓：48 · 最新价：$3.6 · 隐波：0.2345%
  • 25328
    RCL Call $330
    Call · 行权价 $330 · 到期 2026-11-20 · 量/OI：328.29 · 成交量：2,298 · 未平仓：7 · 最新价：$10.05 · 隐波：0.4077%
  • 26313
    QBTS Call $22
    Call · 行权价 $22 · 到期 2026-10-02 · 量/OI：313.38 · 成交量：4,074 · 未平仓：13 · 最新价：$0.56 · 隐波：0.7953%
  • 27313
    TJX Call $138
    Call · 行权价 $138 · 到期 2026-08-28 · 量/OI：313.2 · 成交量：1,566 · 未平仓：5 · 最新价：$1 · 隐波：0.301%
  • 28312
    NN Call $27
    Call · 行权价 $27 · 到期 2026-10-16 · 量/OI：312.5 · 成交量：2,500 · 未平仓：8 · 最新价：$0.24 · 隐波：1.0761%
  • 29310
    BMNR Put $65
    Put · 行权价 $65 · 到期 2027-01-15 · 量/OI：310 · 成交量：310 · 未平仓：1 · 最新价：$40.55 · 隐波：0.9844%
  • 30304
    RIVN Call $15.5
    Call · 行权价 $15.5 · 到期 2026-09-18 · 量/OI：304 · 成交量：304 · 未平仓：1 · 最新价：$1.1 · 隐波：0.5395%
  • 31304
    ULTA Put $510
    Put · 行权价 $510 · 到期 2026-09-25 · 量/OI：304 · 成交量：304 · 未平仓：1 · 最新价：$18.53 · 隐波：0.4832%
  • 32300
    META Put $585
    Put · 行权价 $585 · 到期 2026-08-26 · 量/OI：300.29 · 成交量：8,408 · 未平仓：28 · 最新价：$9.95 · 隐波：0.2838%
  • 33272
    NU Put $15.5
    Put · 行权价 $15.5 · 到期 2026-09-18 · 量/OI：272.2 · 成交量：1,361 · 未平仓：5 · 最新价：$0.65 · 隐波：0.3535%
  • 34272
    ZM Call $106
    Call · 行权价 $106 · 到期 2026-10-02 · 量/OI：272 · 成交量：272 · 未平仓：1 · 最新价：$1.35 · 隐波：0.4226%
  • 35270
    SUI Call $125
    Call · 行权价 $125 · 到期 2026-10-16 · 量/OI：270 · 成交量：1,350 · 未平仓：5 · 最新价：$3.9 · 隐波：0.2038%
  • 36255
    SMTC Call $180
    Call · 行权价 $180 · 到期 2027-03-19 · 量/OI：255 · 成交量：255 · 未平仓：1 · 最新价：$23.3 · 隐波：0.8395%
  • 37250
    ZM Call $116
    Call · 行权价 $116 · 到期 2026-10-02 · 量/OI：250 · 成交量：250 · 未平仓：1 · 最新价：$0.36 · 隐波：0.4377%
  • 38250
    BEKE Put $18
    Put · 行权价 $18 · 到期 2026-10-16 · 量/OI：250 · 成交量：5,000 · 未平仓：20 · 最新价：$0.9 · 隐波：0.3088%
  • 39233
    UPS Call $114
    Call · 行权价 $114 · 到期 2026-10-02 · 量/OI：233 · 成交量：233 · 未平仓：1 · 最新价：$0.75 · 隐波：0.2621%
  • 40230
    CLF Put $10
    Put · 行权价 $10 · 到期 2027-09-17 · 量/OI：230.5 · 成交量：461 · 未平仓：2 · 最新价：$1.92 · 隐波：0.6475%
  • 41218
    META Put $580
    Put · 行权价 $580 · 到期 2026-08-26 · 量/OI：217.63 · 成交量：24,375 · 未平仓：112 · 最新价：$5.5 · 隐波：0.2314%
  • 42217
    CBRS Put $155
    Put · 行权价 $155 · 到期 2027-04-16 · 量/OI：217 · 成交量：434 · 未平仓：2 · 最新价：$32.48 · 隐波：0.8817%
  • 43214
    INTU Put $255
    Put · 行权价 $255 · 到期 2026-09-04 · 量/OI：213.5 · 成交量：427 · 未平仓：2 · 最新价：$0.12 · 隐波：0.9066%
  • 44213
    META Put $577.5
    Put · 行权价 $577.5 · 到期 2026-08-31 · 量/OI：213 · 成交量：213 · 未平仓：1 · 最新价：$10.5 · 隐波：0.3769%
  • 45210
    DIS Put $108
    Put · 行权价 $108 · 到期 2026-09-18 · 量/OI：210.04 · 成交量：4,831 · 未平仓：23 · 最新价：$1.53 · 隐波：0.2162%
  • 46208
    BURL Put $335
    Put · 行权价 $335 · 到期 2026-09-25 · 量/OI：208.33 · 成交量：625 · 未平仓：3 · 最新价：$30.8 · 隐波：0.503%
  • 47205
    NFLX Put $42
    Put · 行权价 $42 · 到期 2028-01-21 · 量/OI：205.13 · 成交量：24,000 · 未平仓：117 · 最新价：$1.2 · 隐波：0.4449%
  • 48205
    LUV Call $46
    Call · 行权价 $46 · 到期 2026-09-18 · 量/OI：204.67 · 成交量：614 · 未平仓：3 · 最新价：$0.22 · 隐波：0.3826%
  • 49200
    DLTR Call $155
    Call · 行权价 $155 · 到期 2026-09-04 · 量/OI：200 · 成交量：200 · 未平仓：1 · 最新价：$0.82 · 隐波：0.7774%
  • 50200
    GMAB Call $35
    Call · 行权价 $35 · 到期 2026-10-16 · 量/OI：200 · 成交量：400 · 未平仓：2 · 最新价：$2.2 · 隐波：0.544%
共 50 条热搜查看完整榜单

BBC News

头条
37分钟前更新
共 33 条热搜查看完整榜单

BD Tech Talks

实时热榜
1小时前更新
  • 01
    OpenAI’s Cursor cutoff makes the ultimate business case for open-source AI
    OpenAI’s decision to sever ties with Cursor proves that relying on closed frontier models is an existential vulnerability for application-layer software. The post OpenAI’s Cursor cutoff makes the ultimate business case for open-source AI first appeared on TechTalks .Ben Dickson
  • 02
    Life, death, and the inevitable rise of AI: An argumentative reassessment
    A medical professional claims AI is a new life form; however, equating it with biological life is speculative and largely dismisses the complexities of conscious existence. The post Life, death, and the inevitable rise of AI: An argumentative reassessment first appeared on TechTalks .Alex Kostikov
  • 03
    The silent data leak hidden inside encrypted reasoning traces of frontier AI models
    AI providers tried to hide the internal reasoning of their frontier models. A cryptographic oversight turned that protection into a massive enterprise data leak. The post The silent data leak hidden inside encrypted reasoning traces of frontier AI models first appeared on TechTalks .Ben Dickson
  • 04
    Why the agent harness matters as much as the model in AI security
    Developers often treat agent harnesses as neutral wiring, but new red-teaming research shows that your choice of harness can make or break your AI security. The post Why the agent harness matters as much as the model in AI security first appeared on TechTalks .Ben Dickson
  • 05
    Beyond ReAct: Building the modern AI agent stack for massive tool ecosystems
    Giving an LLM thousands of tools leads to noisy decisions. Learn how to optimize AI agent planning and tool routing without overwhelming the context window. The post Beyond ReAct: Building the modern AI agent stack for massive tool ecosystems first appeared on TechTalks .Ben Dickson
  • 06
    Why Goodfire’s block-sparse featurizers are a breakthrough in AI interpretability
    Current interpretability tools fracture continuous concepts into isolated points. Goodfire's new approach preserves the full shape of AI reasoning. The post Why Goodfire’s block-sparse featurizers are a breakthrough in AI interpretability first appeared on TechTalks .Ben Dickson
  • 07
    Moving beyond passive RAG: How to implement active memory reconstruction for AI agents
    Passive RAG floods LLM context windows with noise. MRAgent’s active memory reconstruction improves reasoning and cuts token costs. The post Moving beyond passive RAG: How to implement active memory reconstruction for AI agents first appeared on TechTalks .Ben Dickson
  • 08
    How self-improving harnesses are rewriting the agent engineering playbook
    With harness engineering becoming a main focus of AI engineering, new frameworks allow AI agents to write their own execution logic and optimize their performance. The post How self-improving harnesses are rewriting the agent engineering playbook first appeared on TechTalks .Ben Dickson
  • 09
    OneOdio Studio Max 2 review: Ultra-low latency headphones for tech enthusiasts
    OneOdio Studio Max 2 is a versatile hybrid headphone with 120-hour battery life and featuring a 2.4GHz transmitter for 9ms latency, multipoint Bluetooth, and dual wired modes. The post OneOdio Studio Max 2 review: Ultra-low latency headphones for tech enthusiasts first appeared on TechTalks .Ben Dickson
  • 10
    How Nvidia’s ASPIRE framework accelerates robot programming with self-improving AI
    ASPIRE and the new era of self-improving AI frameworks are drastically reducing token costs and deployment friction for real-world robotics applications. The post How Nvidia’s ASPIRE framework accelerates robot programming with self-improving AI first appeared on TechTalks .Ben Dickson
  • 11
    How the AI arms race moved from smart models to full-stack infrastructure
    A breakdown of how OpenAI, Nvidia, Google, and Amazon are shifting their development strategies to capture value across every layer of the tech stack. The post How the AI arms race moved from smart models to full-stack infrastructure first appeared on TechTalks .Ben Dickson
  • 12
    Demystifying loop engineering: Get more from AI agents, avoid loopmaxxing
    The complete guide to the new loop engineering trend. Write powerful agentic loops while avoiding loopmaxxing. The post Demystifying loop engineering: Get more from AI agents, avoid loopmaxxing first appeared on TechTalks .Ben Dickson
  • 13
    Why LLMs should stop thinking out loud (and what comes after chain-of-thought)
    Chain-of-Thought prompting is slow, expensive, and largely an illusion. The future of machine reasoning happens in latent space. The post Why LLMs should stop thinking out loud (and what comes after chain-of-thought) first appeared on TechTalks .Ben Dickson
  • 14
    Beyond vibe coding: How Codev 3.0 engineers the AI-powered dev team
    Casual AI prompting breaks down as codebases grow. Codev introduces strict protocols and multi-model reviews to help teams ship maintainable software. The post Beyond vibe coding: How Codev 3.0 engineers the AI-powered dev team first appeared on TechTalks .Ben Dickson
  • 15
    Why the future of agentic AI is all about the harness
    Scaling LLMs hits limits when dealing with agentic AI tasks. For that, we need to look at the harness and the system built around the model(s). The post Why the future of agentic AI is all about the harness first appeared on TechTalks .Ben Dickson
  • 16
    How Cursor’s Composer 2.5 uses self-distillation to beat the frontier LLMs at coding
    A deep look at the self-distillation techniques that make Composer 2.5 such a great coding model (and the hidden tradeoffs they introduce to AI reasoning). The post How Cursor’s Composer 2.5 uses self-distillation to beat the frontier LLMs at coding first appeared on TechTalks .Ben Dickson
  • 17
    Vertical integration as AI infrastructure: What 21D’s full arch implant system teaches us about building autonomous clinical AI
    A technical breakdown of how 21D built an end-to-end autonomous AI pipeline for one of medicine's most complex procedures — and the architectural decisions that made it work The post Vertical integration as AI infrastructure: What 21D’s full arch implant system teaches us about building autonomous clinical AI first appeared on TechTalks .Ben Dickson
  • 18
    Why sandboxing OpenClaw doesn’t stop data exfiltration
    Research into Nvidia’s NemoClaw reveals that sandboxes don't stop AI agents like OpenClaw from leaking data. We need to rethink security from first principles. The post Why sandboxing OpenClaw doesn’t stop data exfiltration first appeared on TechTalks .Ben Dickson
  • 19
    Google brings multi-token prediction Gemma 4 LLMs
    How Gemma 4’s multi-token prediction and community-driven DFlash are speeding up local LLM throughput by 3-6x. The post Google brings multi-token prediction Gemma 4 LLMs first appeared on TechTalks .Ben Dickson
  • 20
    How Memory Sparse Attention scales LLM memory to 100 million tokens
    Memory Sparse Attention (MSA) scales LLM context windows to an unprecedented 100 million tokens while preserving accuracy. The post How Memory Sparse Attention scales LLM memory to 100 million tokens first appeared on TechTalks .Ben Dickson
  • 21
    Claude Code is leaking API keys into public package registries
    A new study reveals how AI coding assistants like Claude Code are quietly hoarding and publishing sensitive API keys to code repositories. The post Claude Code is leaking API keys into public package registries first appeared on TechTalks .Ben Dickson
  • 22
    Anthropic’s MCP vulnerability: When ‘expected behavior’ becomes a supply chain nightmare
    Security researchers have uncovered a massive architectural flaw in Anthropic's Model Context Protocol, exposing millions of AI applications to remote takeovers. The post Anthropic’s MCP vulnerability: When ‘expected behavior’ becomes a supply chain nightmare first appeared on TechTalks .Ben Dickson
  • 23
    The paradox of LLM self-distillation: Faster reasoning, weaker generalization
    Optimizing LLMs for concise answers can destroy their ability to explore alternative solutions on difficult problems. New study reveals the hidden cost of self-distillation. The post The paradox of LLM self-distillation: Faster reasoning, weaker generalization first appeared on TechTalks .Ben Dickson
  • 24
    Why harness engineering is becoming the new AI moat
    The recent leak of Anthropic's Claude Code reveals a hard truth: as LLMs become commoditized, the sophisticated engineering harness built around them is becoming the real moat. The post Why harness engineering is becoming the new AI moat first appeared on TechTalks .Ben Dickson
  • 25
    TopDawg vs Zendrop for US Dropshipping – Which Platform Is Better in 2026?
    By Raphael Korobka In short: For merchants focused exclusively on selling to US customers, TopDawg is usually the stronger pick. Its supplier network is built around US-based fulfillment, and its hands-on support model suits retailers who want a partner that can provide crucial help. Zendrop works well for sellers who need global reach and a […] The post TopDawg vs Zendrop for US Dropshipping – Which Platform Is Better in 2026? first appeared on TechTalks .Contributor
  • 26
    How GhostClaw malware targets the OpenClaw AI agent boom
    As developers rush to run local AI agents on Mac Minis, GhostClaw malware exploits macOS binaries to silently harvest credentials. The post How GhostClaw malware targets the OpenClaw AI agent boom first appeared on TechTalks .Ben Dickson
  • 27
    Why Meta’s V-JEPA 2.1 model is a massive step forward for real-world AI
    AI models have historically struggled to balance motion tracking with spatial detail. Meta’s V-JEPA 2.1 solves this, pushing the boundaries of video self-supervised learning. The post Why Meta’s V-JEPA 2.1 model is a massive step forward for real-world AI first appeared on TechTalks .Ben Dickson
  • 28
    Multi-level AI prompt engineering: A new tool for scientific discovery
    How multi-level prompt engineering and parabolic extrapolation transformed an LLM into a theoretical collaborator, yielding a testable model of the multiverse. The post Multi-level AI prompt engineering: A new tool for scientific discovery first appeared on TechTalks .Alex Kostikov
  • 29
    Why AI won’t kill SaaS
    The recent tech selloff sparked fears of a SaaSpocalypse. Here is why the death of software subscriptions is a myth, and how AI agents are creating a developer boom. The post Why AI won’t kill SaaS first appeared on TechTalks .Ben Dickson
  • 30
    How C-JEPA is teaching AI the physics of the physical world
    By forcing AI to understand cause and effect instead of just predicting pixels, C-JEPA is laying the groundwork for smarter, more predictable autonomous systems. The post How C-JEPA is teaching AI the physics of the physical world first appeared on TechTalks .Ben Dickson
  • 31
    How Databricks’ FlashOptim cuts LLM training memory by 50 percent
    Training large language models usually requires a cluster of GPUs. FlashOptim changes the math, enabling full-parameter training on fewer accelerators. The post How Databricks’ FlashOptim cuts LLM training memory by 50 percent first appeared on TechTalks .Ben Dickson
  • 32
    How sparse attention solves the memory bottleneck in long-context LLMs
    As AI agents take on longer tasks, the KV cache of LLMs has become a massive bottleneck. Discover how sparse attention techniques are freeing up GPU memory. The post How sparse attention solves the memory bottleneck in long-context LLMs first appeared on TechTalks .Ben Dickson
  • 33
    How ‘semantic chaining’ jailbreaks image generation models
    Semantic Chaining exploits the fragmented safety architecture of multimodal models, bypassing filters by hiding prohibited intent within a sequence of benign edits. The post How ‘semantic chaining’ jailbreaks image generation models first appeared on TechTalks .Ben Dickson
  • 34
    How Sakana AI’s new technique solves the problems of long-context LLM tasks
    RePo, Sakana AI’s new technique, solves the "needle in a haystack" problem by allowing LLMs to organize their own memory. The post How Sakana AI’s new technique solves the problems of long-context LLM tasks first appeared on TechTalks .Ben Dickson
  • 35
    Smarter trade: How AI turns regulatory burden into competitive edge
    Stop reacting to compliance violations and start preventing them. See how AI empowers organizations to turn regulatory discipline into an engine for innovation and growth. The post Smarter trade: How AI turns regulatory burden into competitive edge first appeared on TechTalks .Contributor
  • 36
    Recursive Language Models: A new framework for infinite context in LLMs
    Brute-forcing larger context windows is hitting a mathematical wall. Here is how MIT’s new framework solves "context rot" to process 10 million tokens and beyond. The post Recursive Language Models: A new framework for infinite context in LLMs first appeared on TechTalks .Ben Dickson
  • 37
    Microsoft’s new Rho-alpha model brings tactile sensing to robotics
    Microsoft’s Rho-Alpha upgrades Vision-Language-Action models with tactile data to bridge the gap between semantic reasoning and low-level motor control. The post Microsoft’s new Rho-alpha model brings tactile sensing to robotics first appeared on TechTalks .Ben Dickson
  • 38
    Vulnerability in Perplexity’s BrowseSafe shows why single models can’t stop prompt injection
    Lasso Security compromised Perplexity’s BrowseSafe guardrail model for AI browsers, proving that "out-of-the-box" tools fail to stop prompt injection attacks. The post Vulnerability in Perplexity’s BrowseSafe shows why single models can’t stop prompt injection first appeared on TechTalks .Ben Dickson
  • 39
    How test-time training allows models to ‘learn’ long documents instead of just caching them
    By treating language modeling as a continual learning problem, the TTT-E2E architecture achieves the accuracy of full-attention Transformers on 128k context tasks while matching the speed of linear models. The post How test-time training allows models to ‘learn’ long documents instead of just caching them first appeared on TechTalks .Ben Dickson
  • 40
    VL-JEPA is a lean, fast vision-language model that rivals the giants
    Meta’s VL-JEPA outperforms massive vision-language models on world modeling tasks by learning to predict "thought vectors" instead of text tokens. The post VL-JEPA is a lean, fast vision-language model that rivals the giants first appeared on TechTalks .Ben Dickson
  • 41
    The evolution of LLM tool-use from API calls to agentic applications
    A look at the evolution of LLM tool-use, from supervised fine-tuning to Reinforcement Learning (RLVR) and agentic applications in large and specialized models. The post The evolution of LLM tool-use from API calls to agentic applications first appeared on TechTalks .Ben Dickson
  • 42
    URM shows how small, recurrent models can outperform big LLMs in reasoning tasks
    The key to solving complex reasoning isn't stacking more transformer layers, but refining the "thought process" through efficient recurrent loops. The post URM shows how small, recurrent models can outperform big LLMs in reasoning tasks first appeared on TechTalks .Ben Dickson
  • 43
    The hidden architecture behind AI systems that don’t break under growth
    Most systems break at 100x growth. Real scalability depends on architecture, data quality, and organizational design, not just writing better code. The post The hidden architecture behind AI systems that don’t break under growth first appeared on TechTalks .Contributor
  • 44
    A few interesting observations on Gemini 3 Flash
    Google didn’t reveal a lot of information about its Gemini 3 Flash model. So we had to speculate a lot on what is going on under the hood. The post A few interesting observations on Gemini 3 Flash first appeared on TechTalks .Ben Dickson
  • 45
    How Nvidia changed the open source AI game with Nemotron 3
    As the industry shifts from chatbots to multi-agent workflows, Nvidia's Nemotron 3 offers a blueprint for efficient, long-context reasoning. The post How Nvidia changed the open source AI game with Nemotron 3 first appeared on TechTalks .Ben Dickson
  • 46
    Why AI benchmarks are broken
    AI labs are racing to overtake each other on key industry benchmarks. But this intense race has stripped the benchmarks of most of their value. The post Why AI benchmarks are broken first appeared on TechTalks .Ben Dickson
  • 47
    Salesforce tackles the ‘brittleness’ of web agents with new WALT framework
    WALT abstracts away the chaos of dynamic layouts, allowing AI to focus on high-level planning instead of low-level clicks. The post Salesforce tackles the ‘brittleness’ of web agents with new WALT framework first appeared on TechTalks .Ben Dickson
  • 48
    Beyond raw intelligence: How Poetiq cracked the ARC-AGI-2 benchmark
    The verified solution achieves 54% accuracy on the semi-private test set, outperforming Gemini 3 Deep Think at less than half the cost. The post Beyond raw intelligence: How Poetiq cracked the ARC-AGI-2 benchmark first appeared on TechTalks .Ben Dickson
  • 49
    SOUNDPEATS Clip1 review: Open-ear audio with all-day comfort
    SOUNDPEATS Pearl Clip1 are affordable clip-on earbuds with a secure fit and surprisingly rich, high-resolution audio, making them an excellent choice for listeners who value comfort and situational awareness. The post SOUNDPEATS Clip1 review: Open-ear audio with all-day comfort first appeared on TechTalks .Ben Dickson
  • 50
    What makes DeepSeek-V3.2 so efficient?
    DeepSeek-V3.2 is a top-5 LLM, sitting next to the likes of Grok 4 and GPT-5. But what is more impressive is its efficiency. The post What makes DeepSeek-V3.2 so efficient? first appeared on TechTalks .Ben Dickson
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Berkeley RDI

实时热榜
33分钟前更新
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Big Think

实时热榜
47分钟前更新
  • 01
    How to build a leadership development program that actually works
    Most leadership development programs fail quietly. Designed to look great on paper, rarely built to change behavior in practice. Jessica Lane, Director of Enablement and Communications at ScentAir, knows this better than most. She’s built something that works with a “small but mighty” L&D team, a limited budget, and a CEO who’s completely bought-in. This is what she learned about building a leadership development program that actually works. Why most programs fail before they start The failure uColin DeVoe
  • 02
    This physics trick allows you to beat the speed of light
    In our Universe, there are a few rules that everything must obey. Energy, momentum, and angular momentum are always conserved whenever any two quanta interact. The physics of any system of particles moving forward in time is identical to the physics of that same system reflected in a mirror, with particles exchanged for antiparticles, where the direction of time is reversed. And there’s an ultimate cosmic speed limit that applies to every object: nothing can ever exceed the speed of light in a vEthan Siegel
  • 03
    The “perfect cosmological principle” isn’t true for our Universe
    Back in 1923, an unprecedented scientific revolution occurred. Hubble’s discovery of a Cepheid variable in the Andromeda galaxy, M31, opened up the Universe to us, giving us the observational evidence we needed for galaxies beyond the Milky Way and leading us, in short order, to the discovery of the expanding Universe. Credits : NASA, ESA and the Hubble Heritage Team (STScI/AURA); Illustration via NASA, ESA, and Z. Levay (STScI) Distances to individual stars were measured beyond the Milky Way. EEthan Siegel
  • 04
    Starts With A Bang podcast #133 – The Milky Way’s center
    Here in our Universe, there are all sorts of places where stars are actively forming right now. Our galaxy is going through a relatively quiet phase at present as far as star-formation is concerned, but that rate was much higher in the past: perhaps 30 (or more) times higher than what it is today. If we want to understand what our galaxy was like earlier on, we have two ways to go about it: look farther away, which has the disadvantage that we can’t really observe those places in such great detaEthan Siegel
  • 05
    Ask Ethan: Are there really charm quarks inside the proton?
    At the start of the 20th century, we were still figuring out what the structure of matter was. We knew everything was made up of atoms, and that there were negatively charged electrons within them, but the rest of the atom was a mystery. Over the course of the past 125 years, we subsequently learned that there was a small, massive, positively charged nucleus anchoring every atom. That nucleus itself is composed of nucleons — protons and neutrons — with each one itself made up of quarks and gluonEthan Siegel
  • 06
    The science, medicine, and mythology of menstruation and menopause
    OBGYN and author Dr. Jen Gunter explains what’s actually happening inside the body during menstruation and menopause, why so much of what we’ve been told is wrong, and why that information gap has been weaponized against half the population. This video The science, medicine, and mythology of menstruation and menopause is featured on Big Think .Dr. Jen Gunter
  • 07
    How to make difficult decisions, according to philosophy
    Every now and then, life asks us a question with no easy answer. Which career should we pursue? Should we have children? Should we move to the coast or closer to our friends? We gather information, read testimonials, and exhaustively research both options. One path seems better in some ways, the other seems better in others, and we find ourselves stuck between them. The best answer eludes us. This is what the philosopher Ruth Chang calls a “hard choice.” What makes these kinds of choices hard, CJack Maden
  • 08
    Why mirrors flip left-to-right but not up-and-down
    If you’ve ever looked in a mirror, you’ve likely noticed that everything you see is flipped. When you raise your left hand, your reflection raises their right hand. When you wink with your right eye, your reflection’s left eye winks back. And if you write a message and hold it up, you’ll see your reflection hold up the identical sign, but everything appears backward, even the individual letters themselves. It appears that everything you see reflected in the mirror has their left-and-right reversEthan Siegel
  • 09
    The rule of 20%: How to find the sweet spot for improved performance
    Talent isn’t a gift we’re born with – it’s a signal we’ve been reading completely wrong. Author Daniel Coyle breaks down the common traits shared by successful people, and why environment, not innate ability, is the variable that ties them all together. This video The rule of 20%: How to find the sweet spot for improved performance is featured on Big Think .Daniel Coyle
  • 10
    We have the knowledge to build a better world. But is that enough?
    “The grand, leading principle, towards which every argument unfolded in these pages directly converges, is the absolute and essential importance of human development in its richest diversity.” — Wilhelm von Humboldt Knowledge, especially when shared and collectively held, is essential to human flourishing — as Humboldt emphasizes in the [quote above], which was relayed by John Stuart Mill in the epigraph to On Liberty . Knowledge is not an end in itself. It is an instrument for achieving societyDaron Acemoglu
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哔哩哔哩热搜

实时热榜
33分钟前更新
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40分钟前更新
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Binance

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    现价：1.00026000 USDT · 24h 涨跌：0.023% · 24h 成交额：2807945943.04166000 USDT
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    现价：78330.00000000 USDT · 24h 涨跌：-1.511% · 24h 成交额：1321327454.86176730 USDT
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    现价：2472.04000000 USDT · 24h 涨跌：-1.101% · 24h 成交额：579342328.04016800 USDT
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    现价：103.08000000 USDT · 24h 涨跌：-2.285% · 24h 成交额：204242642.52911000 USDT
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    现价：1158.01000000 USDT · 24h 涨跌：-3.121% · 24h 成交额：193051418.78342000 USDT
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    现价：0.99995000 USDT · 24h 涨跌：0.001% · 24h 成交额：164233112.38087000 USDT
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    现价：1.39700000 USDT · 24h 涨跌：-0.795% · 24h 成交额：136702256.18722000 USDT
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    现价：8.04200000 USDT · 24h 涨跌：0.714% · 24h 成交额：41800002.74502000 USDT
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    现价：2.28600000 USDT · 24h 涨跌：-3.950% · 24h 成交额：38339780.00210000 USDT
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    现价：0.21800000 USDT · 24h 涨跌：-2.022% · 24h 成交额：33607631.20781000 USDT
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    现价：6.26600000 USDT · 24h 涨跌：9.297% · 24h 成交额：32014303.42697000 USDT
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    现价：55.32000000 USDT · 24h 涨跌：-5.258% · 24h 成交额：31299972.12168000 USDT
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    现价：0.15930000 USDT · 24h 涨跌：-6.678% · 24h 成交额：30689703.73032700 USDT
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    现价：253.20000000 USDT · 24h 涨跌：-4.561% · 24h 成交额：24822766.60873000 USDT
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    现价：0.00000363 USDT · 24h 涨跌：-1.626% · 24h 成交额：22405106.48471379 USDT
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    现价：0.00822200 USDT · 24h 涨跌：-7.180% · 24h 成交额：12175362.05770600 USDT
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Bloomberg

头条
39分钟前更新
共 20 条热搜查看完整榜单
10小时前更新
  • 01
    3 Takeaways After Debuting Stretch at MODEX 2022 | Boston Dynamics
    Boston Dynamics commercially launched Stretch, our autonomous robot for the warehouse, at MODEX 2022 in Atlanta in late March. At demos in the booth each day, crowds watched as the robots demonstrated one of the most common and difficult to solve challenges in logistics today: truck unloading.mrodin@bostondynamics.com (Boston Dynamics Team)
  • 02
    Doing More with Spot | Boston Dynamics
    In addition to Spot’s revolutionary mobility, one of its most important attributes is that the robot is designed as a scalable platform that is constantly evolving and expanding on the number of dull, dirty and dangerous jobs it can handle for our customers.mrodin@bostondynamics.com (Boston Dynamics Team)
  • 03
    3 Ways Robots See the World | Boston Dynamics
    Although we are all familiar with the five senses humans use to perceive our surroundings, for robots, these senses look a little different. Robots are rapidly becoming more prevalent in our everyday lives which can take a plethora of forms, from industrial applications, to delivery drones to robotic waiters. No matter what the role, these robots require sensors of all sorts to see the environment around them. The combination of cameras, LiDAR and gas sensors, together play a vital role in inforDonovan Chew
  • 04
    How Much Radiation Can Spot Withstand? | Boston Dynamics
    Limiting exposure to radiation is a top priority for nuclear generators, and organizations are looking increasingly to agile mobile robots to keep their workforce safe. Boston Dynamics Spot allows customers to automate inspection tasks and map the presence of radiation on site. Additionally, operators are able to perform manual inspections remotely, either using the tablet controller from a safe distance, or Scout desktop software.mrodin@bostondynamics.com (Boston Dynamics Team)
  • 05
    What Makes an Effective Research Robot? | Boston Dynamics
    Robots are used for a host of different research topics and applications, from studying human-robot interaction to collecting samples in inhospitable environments to developing new commercial applications of robotics and artificial intelligence. All of these different research goals may require unique capabilities or specifications, but there are some consistent factors for what makes an effective robot in a research context. First and foremost, a research robot needs to serve the research; a romrodin@bostondynamics.com (Boston Dynamics Team)
  • 06
    A New Approach to Predictive Maintenance Challenges | Boston Dynamics
    Effective maintenance programs are vital in manufacturing, energy and utilities, and other asset-intensive industries—preventing equipment failures that lead to costly downtime and repairs. Smart organizations have shifted toward predictive maintenance strategies. Instead of periodically checking assets and replacing parts on fixed schedules, companies are now using artificial intelligence (AI) to identify warning signs of impending issues before they cause damage or outages. This approach can hBob Ochiai
  • 07
    What to Do with a Legged Robot in Academia and Research
    Spot’s easy mobility, along with a host of other benefits, has made it a popular choice in academia and research institutions. The ready-out-of-the-box quadruped robot helps researchers focus on their objectives, explore tough problems, and experiment with the many ways robotics can positively impact people’s lives. Here are just a few ways that educational and research organizations are working with Spot today.mrodin@bostondynamics.com (Boston Dynamics Team)
  • 08
    Unlock the Data that Matters Most
    As a quadruped robot, Spot can operate virtually anywhere a person can—going up and down stairs, indoors or outdoors, and through cramped or confined spaces. While this mobility can be impressive on its own, its real value is in automating sensing and inspection in areas inaccessible with wheeled or tracked robots and drones. You can send Spot into areas designed for people, that are unstructured, or even hazardous, to collect the data you need to understand what's going on in your facility or amrodin@bostondynamics.com (Boston Dynamics Team)
  • 09
    Break Through Supply Chain Blocks with Automated Container Unloading
    Customers finding bare spots on grocery store shelves or waiting months instead of weeks for a furniture delivery are feeling the ripple effects of supply chain disruptions—with more shortages and delays anticipated as the holiday season approaches. Much of the merchandise is out there, stalled in cargo ports loaded with shipping containers at unprecedented volumes. Labor shortages have slowed the pace of unloading containers and warehouses to a crawl, and ports on both U.S. coasts have requiredmrodin@bostondynamics.com (Boston Dynamics Team)
  • 10
    What is Dynamic Sensing?
    Artificial intelligence is changing the way businesses operate. AI systems demand a continuous flow of repeatable data that’s difficult to collect on physical sites. Today, the health of equipment in facilities is monitored through a mix of fixed sensors and operator rounds. These sensors are limited in perspective, expensive to scale, and can’t adapt to changes. Companies make up the data deficit by spending human resources on tedious data collection. But people are too inconsistent at data colmrodin@bostondynamics.com (Boston Dynamics Team)
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