Oracle Gece Arastirma — 2026-06-29

Curado por Mahsum Aktaş · Escaneo diario automatizado del sector de IA

Oracle Gece Arastirma — 2026-06-29

Otomatik derleme | v3 pipeline | 5.014 ham kaynak | 4.993 benzersiz item | 85 benzersiz kaynak | 5/5 kaynak ailesi kapsandi

Gunun Ozeti

Bugunun ana ekseni AI otomasyonunun "insani tamamen cikar" vaadinden operasyonel kalite ve guvenlik disiplinine geri donmesiydi: Ford'un deneyimli muhendisleri geri cagirmasi, coding agent'larda insan review'un azalmasi ve "smelly config" riski ayni noktaya isaret ediyor. Kaynak: https://techcrunch.com/2026/06/28/ford-rehires-gray-beard-engineers-after-ai-falls-short/ ve http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=6a4192b2c3fa46e89435da3b4a67e8f5&url=https%3a%2f%2fwww.businessinsider.com%2fai-coding-agents-cursor-human-review-2026-6&c=6599757506363124942&mkt=tr-tr

Model ve altyapi tarafinda edge/on-device agirligi guclendi: Liquid AI LFM2.5-230M, Modular MAX'in Apple silicon GPU destegi ve AWS FinOps Agent, "daha buyuk model" yerine "daha ucuz, daha yakin, daha yonetilebilir inference" hattini one cikardi. Kaynak: https://www.marktechpost.com/2026/06/27/liquid-ai-ships-lfm2-5-230m-with-llama-cpp-mlx-vllm-sglang-and-onnx-support-for-on-device-inference/ ve https://www.infoq.com/news/2026/06/aws-finops-agent/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=AI%2C+ML+%26+Data+Engineering

Regulasyon ve veri sahipligi cephesinde Google'in Meta'nin Gemini kullanimini sinirlamasi, ChatGPT loglarinin dava delili olmasi ve EU AI Act uyum rehberi ayni sinyali veriyor: model erisimi, veri izleri ve governance artik urun mimarisinin parcasi. Kaynak: https://www.cnbc.com/2026/06/28/google-limits-metas-use-of-its-gemini-ai-models-ft-reports.html ve https://www.theverge.com/ai-artificial-intelligence/958751/prosecutors-chatgpt-palisades-wildfire-arson-mistrial

Top 7

1. Ford, AI ile kaliteyi tek basina artiramayinca deneyimli muhendisleri geri cagiriyor; bu, domain uzmanligi olmadan otomasyonun ters tepebilecegine guclu bir vaka. Kaynak: https://techcrunch.com/2026/06/28/ford-rehires-gray-beard-engineers-after-ai-falls-short/
2. Google, Meta'nin Gemini modellerini kullanimini sinirliyor; hyperscaler/model erisimi artik rekabet hukuku ve stratejik tedarik riski haline geliyor. Kaynak: https://www.cnbc.com/2026/06/28/google-limits-metas-use-of-its-gemini-ai-models-ft-reports.html
3. AWS FinOps Agent preview'i, cloud maliyet analizini agent is akisi haline getiriyor; AI spend kontrolu artik tekil dashboard degil, otomatik soru-cevap ve aksiyon katmani. Kaynak: https://www.infoq.com/news/2026/06/aws-finops-agent/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=AI%2C+ML+%26+Data+Engineering
4. Liquid AI LFM2.5-230M, llama.cpp, MLX, vLLM, SGLang ve ONNX destegiyle edge inference paketini genisletiyor; kucuk model pazari canli. Kaynak: https://www.marktechpost.com/2026/06/27/liquid-ai-ships-lfm2-5-230m-with-llama-cpp-mlx-vllm-sglang-and-onnx-support-for-on-device-inference/
5. ChatGPT loglari Palisades yangini davasinda delil olarak kullaniliyor; AI sohbet gecmisi artik hukuki discovery ve risk yonetimi konusu. Kaynak: https://www.theverge.com/ai-artificial-intelligence/958751/prosecutors-chatgpt-palisades-wildfire-arson-mistrial
6. "Tail Control" yazisi agentic workflow guvenilirliginde ortalama kalite yerine gecikme varyansi ve tail risk yonetimini one cikariyor. Kaynak: https://towardsdatascience.com/tail-control-the-counterintuitive-engineering-of-reliable-agentic-workflows/
7. Suno Spark, AI muzik sirketlerinin sadece generation araci degil, sanatci edinim ve dagitim platformu olmaya calistigini gosteriyor. Kaynak: https://www.theverge.com/ai-artificial-intelligence/958801/suno-launches-spark-incubator-program-to-feed-independent-artists-to-its-ai-machine

KAT-1 LLM & Model Guncellemeleri

• Liquid AI, LFM2.5-230M ile on-device inference icin coklu runtime destegi verdi; mobil ve lokal ajanlar icin kucuk model performansi izlenmeli. Kaynak: https://www.marktechpost.com/2026/06/27/liquid-ai-ships-lfm2-5-230m-with-llama-cpp-mlx-vllm-sglang-and-onnx-support-for-on-device-inference/
• Sina'nin VibeThinker-3B modeli, reasoning'in sikistirilabilir ama factual bilginin daha zor tasinabilir oldugunu one cikaran kucuk model hattina yeni sinyal ekledi. Kaynak: https://the-decoder.com/sinas-open-model-vibethinker-3b-aims-to-show-reasoning-compresses-well-but-factual-knowledge-doesnt/
• Baidu Unlimited-OCR, uzun ufuklu OCR ve vision-language extraction icin HF trending modellerinde yuksek gorunurluk aldi. Kaynak: https://huggingface.co/baidu/Unlimited-OCR
• GLM-5.2 ekosistemi, orijinal model, Unsloth GGUF ve NVIDIA NVFP4 quantization varyantlariyla inference optimizasyonu tarafinda yayiliyor. Kaynak: https://huggingface.co/zai-org/GLM-5.2 ve https://huggingface.co/nvidia/GLM-5.2-NVFP4

KAT-2 Arastirma & Paper'lar

• "Co-Failure Ceiling" calismasi, routing/voting/mixture-of-agents sistemlerinde modeller ayni yerde yaniliyorsa ensemble kazancinin tavana carptigini gosteriyor. Kaynak: https://huggingface.co/papers/2606.27288
• "Running the Gauntlet", agent benchmark'lerinin tanidik ortamlara asiri uyumlanmasi riskini ve farkli ortamda gercek kabiliyet olcumunu tartisiyor. Kaynak: https://huggingface.co/papers/2606.14397
• Information-Aware KV Cache Compression, uzun reasoning sirasinda KV cache maliyetini bilgi degeriyle azaltmayi hedefliyor. Kaynak: https://huggingface.co/papers/2606.26875
• CAVEWOMAN, "kisa yaz token kurtarir" varsayimini test ediyor; prompt ve output compression etkisinin kanala gore degistigini gosteriyor. Kaynak: https://huggingface.co/papers/2606.24083

KAT-3 Araclar & Framework'ler

• AWS FinOps Agent, maliyet anomalisi ve kaynak optimizasyonunu dogrudan agent tabanli arastirma is akisi olarak paketliyor. Kaynak: https://www.infoq.com/news/2026/06/aws-finops-agent/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=AI%2C+ML+%26+Data+Engineering
• Wayfinder Router, local ve hosted LLM arasinda deterministik query routing yaklasimi sunuyor; maliyet/mahremiyet split'i icin pratik sinyal. Kaynak: https://github.com/itsthelore/wayfinder-router
• OCRmyPDF tutorial'i, taranmis PDF'leri aranabilir PDF/A ve sidecar metne donusturen batch pipeline'i detaylandiriyor. Kaynak: https://www.marktechpost.com/2026/06/28/ocrmypdf-tutorial-convert-scanned-documents-into-searchable-pdf-a-files-with-sidecar-text-extraction-and-batch-processing/
• Modular MAX, Apple silicon GPU destegiyle lokal inference ve Mojo/MAX toolchain tarafinda macOS gelistirici yolunu aciyor. Kaynak: https://forum.modular.com/t/max-models-can-now-run-on-apple-silicon-gpus/3283

KAT-4 Acik Kaynak

• google-labs-code/design.md, coding agent'lar icin tasarim sistemi bilgisini kalici ve yapilandirilmis dosya formatina tasiyor. Kaynak: https://github.com/google-labs-code/design.md
• topoteretes/cognee, agent'lar icin self-hosted knowledge graph ve long-term memory altyapisi olarak trend oldu. Kaynak: https://github.com/topoteretes/cognee
• anomalyco/opencode, open-source coding agent pazarinda alternatif CLI/agent deneyimi sunuyor. Kaynak: https://github.com/anomalyco/opencode
• Fission-AI/OpenSpec, AI coding assistant'lar icin spec-driven development akisini hafif bir framework olarak konumlandiriyor. Kaynak: https://github.com/Fission-AI/OpenSpec

KAT-5 Endustri & Sirketler

• Ford vakasi, AI otomasyonunun domain uzmanligini ikame etmedigi yerde kalite borcu urettigini gosteriyor. Kaynak: https://techcrunch.com/2026/06/28/ford-rehires-gray-beard-engineers-after-ai-falls-short/
• Google'in Meta'ya Gemini erisim kisiti, model tedarik zinciri riskini buyuk platformlar icin bile kritik hale getiriyor. Kaynak: https://www.cnbc.com/2026/06/28/google-limits-metas-use-of-its-gemini-ai-models-ft-reports.html
• General Intuition, video oyun verisiyle spatial AI/intuitive behavior egitimi iddiasiyla 320 milyon dolar yatirim ve 2.3 milyar dolar degerleme sinyali verdi. Kaynak: https://news.google.com/rss/articles/CBMizAFBVV95cUxQemZOTE5kTzVOLTZ2YUh2X0NlTDEyZjRBUWJRUlBpTzJkV2ZvVTlZQjUteUFWR2FIWGNKTjNEODNJY0ZvRHZxTFlQQmhDZFFMZC1mRV93ZDFuUzYtUEx0ZmdyTDhEMTMxM0MzSFBOWHA2WHlHdjZ5VzVjQ3FFVHRRUDJkeHFQNTNwclBZVnkxXzlnZVVNdkF3RFFSRHZTWlVJR21UaUN4LWhKN00waVdPam9WQU5xcEZjbGtqOWRlbklUWHcxemotWnY0elM?oc=5
• Micron, AI bellek talebi nedeniyle "sonraki Nvidia" anlatilarinda one cikiyor; memory supply chain AI ekonomisinin dar bogazi olmaya devam ediyor. Kaynak: https://techcrunch.com/2026/06/28/why-wall-street-thinks-us-memory-maker-micron-is-the-next-nvidia/

KAT-6 AI Agent'lar

• "Tail Control", agentic workflow'larda ortalama latency yerine p95/p99 davranisin urun kalitesini belirledigini savunuyor. Kaynak: https://towardsdatascience.com/tail-control-the-counterintuitive-engineering-of-reliable-agentic-workflows/
• Business Insider haberine gore AI coding agent'lar uretime daha dogrudan girerken insan code review azalıyor; bu, hiz kadar governance riski demek. Kaynak: http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=6a4192b2c3fa46e89435da3b4a67e8f5&url=https%3a%2f%2fwww.businessinsider.com%2fai-coding-agents-cursor-human-review-2026-6&c=6599757506363124942&mkt=tr-tr
• "Smelly config files" basligi, agent talimat dosyalarinda context bloat, skill leakage ve celiskili instruction risklerini pratik bir taxonomy'ye tasiyor. Kaynak: http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=6a4192b2c3fa46e89435da3b4a67e8f5&url=https%3a%2f%2fwww.infoworld.com%2farticle%2f4187057%2fai-coding-agents-may-be-getting-bad-instructions-from-smelly-config-files.html&c=138036411921572764&mkt=tr-tr
• "Are We Ready For An Agent-Native Memory System?" paper'i, agent memory'nin basit RAG'den veri yonetim sistemi problemine evrildigini soyluyor. Kaynak: https://huggingface.co/papers/2606.24775

KAT-7 Multimodal

• Krea-2 Turbo ve Krea-2 Raw, text-to-image tarafinda HF uzerinde gorunurluk kazandi; lisans ve workflow entegrasyonu ayrica izlenmeli. Kaynak: https://huggingface.co/krea/Krea-2-Turbo ve https://huggingface.co/krea/Krea-2-Raw
• Qwen-AgentWorld-35B-A3B, world-model/agent/environment-simulation etiketleriyle multimodal agent arastirmasi icin izleme listesine girdi. Kaynak: https://huggingface.co/Qwen/Qwen-AgentWorld-35B-A3B
• NagaTranslate, dusuk kaynakli Nagaland creole dilleri icin Whisper, VITS ve LLM tabanli ceviri/ses pipeline'i kuruyor. Kaynak: https://www.reddit.com/r/MachineLearning/comments/1uhlvjv/nagatranslate_building_a_translation_and_voice/
• TryOnCrafter, video virtual try-on icin renderable 4D proxy yaklasimi oneriyor. Kaynak: https://huggingface.co/papers/2606.26092

KAT-8 Robotik & Embodied AI

• IEEE Spectrum, AI ile RF chip design surecinde geleneksel "dark art" know-how'un model destekli tasarima acildigini anlatiyor. Kaynak: https://spectrum.ieee.org/ai-radio-chip-design
• openpilot, GitHub trending'de robotics/driver assistance tarafinda yuksek ilgi gormeye devam ediyor. Kaynak: https://github.com/commaai/openpilot
• EBench, genel mobil manipülasyon politikalarini tek basari orani yerine elemental diagnosis ile olcmeyi oneriyor. Kaynak: https://huggingface.co/papers/2606.18239
• Dashcam videosundan GPS olmadan geolocation projesi, embodied/perception pipeline'larinda video-only localization'in topluluk ilgisini gosteriyor. Kaynak: https://www.reddit.com/r/MachineLearning/comments/1ufx8nx/showcase_geolocating_a_dashcam_video_without_gps/

KAT-9 Topluluk & Rehberler

• NanoEuler, GPT-2 olceginde modeli saf C/CUDA ile sifirdan kurma ilgisini HN/Mastodon hattinda yukseltti. Kaynak: https://mastodon.social/@h4ckernews/116829586061217291
• pybench, training/config degisikliklerini istatistiksel regresyon testleriyle yakalama fikrini topluluga tasidi. Kaynak: https://www.reddit.com/r/MachineLearning/comments/1ugv7u3/i_silently_break_training_codes_or_configs_so_i/
• RL reward function debugger projesi, reward hacking'i egitim sirasinda tespit etmeye odaklaniyor. Kaynak: https://www.reddit.com/r/MachineLearning/comments/1uga687/a_debugger_for_rl_reward_functions_that_detects/
• Kuma, PyTorch modellerini self-contained WebGPU executable'a derleme fikrini tartismaya acti. Kaynak: https://www.reddit.com/r/MachineLearning/comments/1ufl9tu/kuma_compiling_pytorch_models_into_selfcontained/

SECURITY

• "What Intermediate Layers Know" paper'i, jailbreak tespitini ara katman entropy dinamiklerinden okumayi oneriyor. Kaynak: https://huggingface.co/papers/2606.25182
• "When Lower Privileges Suffice" paper'i, LLM agent'larin gereksiz yuksek yetkili tool secme egilimini guvenlik riski olarak inceliyor. Kaynak: https://huggingface.co/papers/2606.20023
• AI coding agent'larda human review'un azalmasi, supply-chain ve instruction injection risklerini dogrudan production riskine ceviriyor. Kaynak: http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=6a4192b2c3fa46e89435da3b4a67e8f5&url=https%3a%2f%2fwww.businessinsider.com%2fai-coding-agents-cursor-human-review-2026-6&c=6599757506363124942&mkt=tr-tr
• SimpleX Chat'in kimliksiz mesajlasma mimarisi, AI donemi veri minimizasyonu ve privacy-by-design tartismalarina acik kaynak ornek sunuyor. Kaynak: https://github.com/simplex-chat/simplex-chat

REGULATION

• EU AI Act compliance rehberi, risk tier, son tarihler ve engineering governance aksiyonlarini product pipeline'a bagliyor. Kaynak: https://www.docker.com/blog/eu-ai-act-compliance/
• ChatGPT loglarinin ceza davasinda delil olarak kullanilmasi, AI sohbet kayitlari icin retention, legal hold ve privacy politikasini kritiklestiriyor. Kaynak: https://www.theverge.com/ai-artificial-intelligence/958751/prosecutors-chatgpt-palisades-wildfire-arson-mistrial
• Google-Meta Gemini kisiti, model API erisiminin rekabet ve stratejik bagimlilik meselesi oldugunu gosteriyor. Kaynak: https://www.cnbc.com/2026/06/28/google-limits-metas-use-of-its-gemini-ai-models-ft-reports.html

AI-SCIENCE

• AI in mathematics tartismasi, matematikcinin rolunu ispat bulan kisiden problem kuran/yorumlayan kisiye kaydiriyor. Kaynak: https://spectrum.ieee.org/ai-in-mathematics
• AI ile RF chip design, fiziksel tasarim sezgisinin veri/model destekli arama problemine donustugunu gosteriyor. Kaynak: https://spectrum.ieee.org/ai-radio-chip-design
• EO-WM, Earth Observation forecast icin fiziksel bilgiyle desteklenen probabilistic world model oneriyor. Kaynak: https://huggingface.co/papers/2606.27277
• Autodata, agent'i veri bilimci gibi kullanip kaliteli synthetic training/evaluation data uretmeyi hedefliyor. Kaynak: https://huggingface.co/papers/2606.25996

INFRA

• Micron haberleri, AI compute ekonomisinde GPU kadar memory arzinin da kritik dar bogaz oldugunu hatirlatiyor. Kaynak: https://techcrunch.com/2026/06/28/why-wall-street-thinks-us-memory-maker-micron-is-the-next-nvidia/
• AWS FinOps Agent, cloud spend ve AI infra maliyetlerini agent destekli operasyon konusuna ceviriyor. Kaynak: https://www.infoq.com/news/2026/06/aws-finops-agent/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=AI%2C+ML+%26+Data+Engineering
• MAX Apple silicon GPU destegi, Mac lokal compute hattini AI gelistirme icin daha ciddi hale getiriyor. Kaynak: https://forum.modular.com/t/max-models-can-now-run-on-apple-silicon-gpus/3283
• Orbital data center hype'ina gelen supheler, AI compute icin enerji/latency/fizibilite sorularinin daha sert sorulacagini gosteriyor. Kaynak: https://techcrunch.com/2026/06/27/softbanks-ceo-isnt-the-only-one-with-questions-about-elon-musks-orbital-data-center-hype/

SAFETY

• PrivacyAlign, agent kararlarinda kullanici baglamina duyarlı gizlilik hizalamasi problemini tanimliyor. Kaynak: https://huggingface.co/papers/2606.21710
• "Do Thinking Tokens Help with Safety?" paper'i, reasoning modunun guvenlik performansini otomatik garanti etmedigini test ediyor. Kaynak: https://huggingface.co/papers/2606.25013
• "Forecasting Future Behavior as a Learning Task", guvenin aciklamadan cok gelecekteki davranisi tahmin edebilme kabiliyetine bagli oldugunu tartisiyor. Kaynak: https://huggingface.co/papers/2606.11445
• "Deployment Awareness Matters More Than Evaluation Awareness", modelin testte oldugunu bilmesinden cok gercek deployment'ta oldugunu ayirt etmesinin daha riskli oldugunu savunuyor. Kaynak: https://www.alignmentforum.org/posts/XP794SHDuXYfWLrvJ/deployment-awareness-matters-more-than-evaluation-awareness

WATCHLIST

• LFM2.5-230M: on-device agent runtime'lari icin performans ve lisans durumu izlenecek. Kaynak: https://www.marktechpost.com/2026/06/27/liquid-ai-ships-lfm2-5-230m-with-llama-cpp-mlx-vllm-sglang-and-onnx-support-for-on-device-inference/
• Google-Meta Gemini erisim kisiti: model vendor lock-in ve stratejik platform bagimliligi icin takip edilecek. Kaynak: https://www.cnbc.com/2026/06/28/google-limits-metas-use-of-its-gemini-ai-models-ft-reports.html
• Agent config hygiene: instruction bloat ve celiskili config'ler icin internal lint ihtiyaci dogdu. Kaynak: http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=6a4192b2c3fa46e89435da3b4a67e8f5&url=https%3a%2f%2fwww.infoworld.com%2farticle%2f4187057%2fai-coding-agents-may-be-getting-bad-instructions-from-smelly-config-files.html&c=138036411921572764&mkt=tr-tr
• General Intuition: game data ile spatial intelligence egitimi, robotics/world-model pazarinda yeni yatirim narratifi olabilir. Kaynak: https://news.google.com/rss/articles/CBMizAFBVV95cUxQemZOTE5kTzVOLTZ2YUh2X0NlTDEyZjRBUWJRUlBpTzJkV2ZvVTlZQjUteUFWR2FIWGNKTjNEODNJY0ZvRHZxTFlQQmhDZFFMZC1mRV93ZDFuUzYtUEx0ZmdyTDhEMTMxM0MzSFBOWHA2WHlHdjZ5VzVjQ3FFVHRRUDJkeHFQNTNwclBZVnkxXzlnZVVNdkF3RFFSRHZTWlVJR21UaUN4LWhKN00waVdPam9WQU5xcEZjbGtqOWRlbklUWHcxemotWnY0elM?oc=5

TRENDS

• AI Agents toplam 548 mention ile spike konumunda; agent konusu artik framework'ten governance, latency, memory ve review disiplinine yayildi. Kaynak: https://towardsdatascience.com/tail-control-the-counterintuitive-engineering-of-reliable-agentic-workflows/
• Anthropic toplam 361 mention ile yuksek gorunurlukte kaldi, fakat bugun yeni tekrar basligi yerine vendor/model erisimi tartismasi Google-Meta eksenine kaydi. Kaynak: https://www.cnbc.com/2026/06/28/google-limits-metas-use-of-its-gemini-ai-models-ft-reports.html
• AI Safety 46 mention ile jailbreak, privacy alignment, tool privilege ve deployment awareness basliklarinda yogunlasti. Kaynak: https://huggingface.co/papers/2606.25182
• Apple 39 mention ile yukseliste; MAX Apple silicon GPU destegi ve on-device model sinyalleri Mac tabanli lokal AI hattini guclendiriyor. Kaynak: https://forum.modular.com/t/max-models-can-now-run-on-apple-silicon-gpus/3283

CikCik Paketi

• "AI slop" tartismasi Suno Spark ve Robin Williams referansli HN basligiyla kulturel zeminde yogunlasti; CikCik icin ton: "AI icerik uretmek degil, dagitim ve guven kurmak zorunda." Kaynak: https://jayacunzo.com/blog/your-move-chief
• HN'de "AI serving just the few" basligi, AI'nin insanligi ele gecirmesinden cok gucun az sayida kurumda toplanmasi riskini tartistirdi. Kaynak: https://news.ycombinator.com/item?id=48701615
• Ford vakasi icin CikCik acisi: "AI yerine insan" degil, "domain uzmanligi olmadan AI kalite uretmez." Kaynak: https://techcrunch.com/2026/06/28/ford-rehires-gray-beard-engineers-after-ai-falls-short/
• Google-Meta Gemini kisiti icin CikCik acisi: "En buyuk sirketler bile model API tedarik riskinden muaf degil." Kaynak: https://www.cnbc.com/2026/06/28/google-limits-metas-use-of-its-gemini-ai-models-ft-reports.html
• Agent config smell konusu icin CikCik acisi: "Kod agent'ina verdigin talimatlar da production config'tir; lint edilmezse sistem davranisini zehirler." Kaynak: http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=6a4192b2c3fa46e89435da3b4a67e8f5&url=https%3a%2f%2fwww.infoworld.com%2farticle%2f4187057%2fai-coding-agents-may-be-getting-bad-instructions-from-smelly-config-files.html&c=138036411921572764&mkt=tr-tr

Oracle Self-Improvement Sinyalleri

• v3 dedupe semantik/state taramasi 4.993 item ile cron penceresini asti; fallback URL/title tekillestirme ile rapor tamamlandi, dedupe script'i icin batch veya cap gerekli. Kaynak: raw-sources/2026-06-29/merged.json
• Social collector 4.176 item uretti ve Twitter fallback kaynaklari rapor havuzunu domine etti; source cap ve recency filter uygulanmali. Kaynak: raw-sources/2026-06-29/social.json
• Search collector 510 item getirdi ama Google News aggregator linkleri canonical URL kalitesini dusuruyor; publish oncesi canonical resolver eklenmeli. Kaynak: raw-sources/2026-06-29/search.json
• Reddit ve Semantic Scholar 429 verdi; rate-limit aware backoff ve cache katmani pipeline guvenilirligini artirir. Kaynak: raw-sources/2026-06-29/academic.json

Kaynak Ozeti

• RSS/news: 188 ham item, TechCrunch, The Verge, The Decoder, CNBC, DonanimHaber ve Technopat agirlikli. Kaynak: raw-sources/2026-06-29/rss.json
• Academic/API: 70 ham item, HF Daily Papers ve HF Trending Models agirlikli; Semantic Scholar 429 nedeniyle eksik. Kaynak: raw-sources/2026-06-29/academic.json
• Community: 70 ham item, GitHub Trending, Lobsters ve r/MachineLearning kapsandi. Kaynak: raw-sources/2026-06-29/community.json
• Search: 510 ham item, Bing News ve Google News sorgulari kapsandi. Kaynak: raw-sources/2026-06-29/search.json
• Social: 4.176 ham item, Mastodon hashtagleri ve Twitter fallback profilleri kapsandi. Kaynak: raw-sources/2026-06-29/social.json
• Coverage: 5/5 kaynak ailesi, 10/10 topic kapsandi; blind spot yok, ancak social ve search baskinligi kalite riski. Kaynak: /tmp/v3-prompt.txt

Dedupe & Kalite Notu

Bu rapordaki ana maddeler onceki 3 gunun raporlarindaki Top/Ozet tekrarlarindan elendi; Mythos, DSpark, Vercel Eve, Dapr, Akrites, OpenAI-Broadcom Jalapeno, Patronus ve Docker MCP/Flowise tekrar edilmedi. Kaynak: reports/2026-06-28.md

Toplam 5.014 ham item islendi, merge sonrasi 4.993 benzersiz item rapor havuzuna alindi. Semantik dedupe cron suresini astigi icin fallback URL/title tekillestirme kullanildi. Kaynak: raw-sources/2026-06-29/unique.json