Oracle Gece Arastirma — 2026-04-27

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

Oracle Gece Arastirma — 2026-04-27

Otomatik derleme | v3 pipeline | son 3 gun ana haberleri tekrar edilmeden | kaynak URL zorunlu secim

Gunun Ozeti

Bugunun ana resmi, frontier yaristan cok deployment gercekligi ve insan-denetimli verimlilik tavaninin konusulmasi. Google’da karmasik kod migration islerinin %75’inin AI ajanlari + muhendis karmasi ile yurudugu iddiasi, buna karsilik 500 investment banker degerlendirmesinde tek bir model cikisinin musteriye dogrudan gonderilmeye hazir bulunmamasi ve insan katilimi oldugunda AI’nin daha iyi sonuc verdigini gosteren kapsamli calisma birlikte okununca, 2026 anlatisi “AI her isi devraldi” degil, “AI is akisini yeniden parcaliyor ama son karar hatti insanda kaliyor” noktasina oturuyor. Kaynaklar: http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=69ee842b43154be094040c10856bb65c&url=https%3a%2f%2findianexpress.com%2farticle%2ftechnology%2fartificial-intelligence%2fgoogle-75-percent-ai-generated-code-sundar-pichai-10656702%2f&c=350596984028401018&mkt=tr-tr | https://the-decoder.com/500-investment-bankers-review-ai-outputs-and-find-none-ready-for-client-delivery/ | https://news.google.com/rss/articles/CBMipgFBVV95cUxNS2JFd0VTdkptX2p3ZFJ1YkNsLW11ckdrUVFNZFVFOUNBT3VBb0JqcGRnRW5nc0hSSXpqbUxFX3AxSmhUaXZ5elJCcnhnRGtLa0piQVlUT2xzT3hfUS1vWEFsT3lITm14bVRzQzFQWXdSbUc4bTFieTE1Sk15emsybU4yVWx4aE91Z3p6Z0dJMjZzUFA4R1Utb2ZDeUhaUmFVbFcyRDZ3?oc=5

Ikinci eksen, policy ve toplumsal risk refleksinin sertlesmesi. Guney Afrika’da taslak ulusal AI politikasinin geri cekilmesi, Manitoba’nin gencler icin sosyal medya ve AI kisiti hamlesi, bir otomobil recall surecinde AI tavsiyesinin hata uretmesi ve “AI bizim anonimligimizi bitirebilir mi?” tartismasi ayni yone isaret ediyor: AI artik yalniz teknoloji urunu degil, kamu kalitesi, tuketici guveni ve vatandas korumasi meselesi. Kaynaklar: https://news.google.com/rss/articles/CBMimwFBVV95cUxPa3QyQ3ltSFVYaXFBVUl1eUxXek16c0RvVEIxcm9td2RoNTdqVHVvYzRTNk8yRjc2bG1wS3J1WGpHV2ZQX0hBbVB0YXY0dkRlTmtXTkFoYUl5U09yWkVMeEJOVmV1RU5vQlBTS2lWVVRrSXZmVDh1VmpHRlJVNVZmOHBUZjhaRF83d19PQUNCLWhfVW1ka2J1NUVxZw?oc=5 | https://news.google.com/rss/articles/CBMiwAFBVV95cUxQZDUweHNHTGJQb3d0VjVkazRvc1hKS3hsd1Vrb1N0cmo0bDBRM1NPTnlmLTZadGZ6ei1rZ1g1RWpDRVB1YWVnUWpfQmhNNEotcWdOY0J1ekZEdGkzdXI1TXg1SXZERTBMd0RaX2RvYlZ4MWxpZDZDdmxKQkIwS21xYkxHbHZrMjhCS0RIRnAwWG13b2RnMEY0enFFYmJJWjZmQXRBRE5Bb1c2eGxHN29NemVXQ19pMy1WMzQ0MXhJYUg?oc=5 | https://news.google.com/rss/articles/CBMiygFBVV95cUxOQk5KOTR5amo5NzAwZG9aNWdqdW1RZ0JfQjhhV0dLdlJJUFozeG9tRDVTcVc1QUxVRjdmNkVZS0lLWWpXQS15R1E4V09PVTVxREx6X0hDbTFleFhiS0t3M01KZy1tMDFpd0xyaUdqS1ZCcHQ4eDByUy1LMl9qR0VPYjJKVGUxWXFZak0wOEh0alJjeFRvckpZWjYyMUhId3NWS05hOU1Gbk9Zd1c0OUFzcHNOYVQwYlh1cFBfSEZOUUlWNERyZDZmRDhn?oc=5 | https://news.google.com/rss/articles/CBMitgFBVV95cUxNRUZIWlZBdE1NdWstUnZkQU01YTBDdER3MHo0bDEzR1FlcVpjLWxlcjBJbmFSMWhFMmpGRGU1TW5acDVqdS1sNDVxRU1zVk5lazRFUmEtRGJBMVRuWDRFNERNeXg5UFZJN3g2djNidGdxaHdNdmZPbGVjcWZnX00yV2xsWlVOQmt6Uy02Y0MwUVltMWpXYUVGSFlrMC1Tdnc4UnFUakQxMFJOSzE4M2E2SWpGWGRmQQ?oc=5

Ucuncu eksen, uygulanabilir guvenlik ve paketlenmis urunlesme. OpenAI’nin on-device calisabilen Privacy Filter modeli, Google’ın Hindistan Vizag AI data center hamlesi, Coachella’nin DeepMind destekli canli eglence deneyleri ve NotebookLM’in slayt/rehber uretim akisi, “tek buyuk model” yerine belirli is akislari icin optimize edilmis urun ve altyapi katmaninin hizlandigini gosteriyor. Kaynaklar: https://openai.com/index/introducing-openai-privacy-filter/ | https://news.google.com/rss/articles/CBMivgFBVV95cUxOR3RfNzlySE9ob2VLenBVeFlkd0wyV1huVGVtSFM4VzdtXzJ1OGRhelY0T29IMmh5RnVrcWhVV1lKbUVhd0xJdXgwZ0ZqM2xKaVlvbnlkX3JiMFladnFPdTlxM0NVQVdzaFNuR25KaG9uSUxPUlhGLW1kSll6Qjh0cDZIMzZQRUY2MlFLMWN3VUZlWDBzako4VG1WSmszXzlOTWhmeWlvSWoyYmVoYko4Q21wak41bjUtbFFzLU9n0gG-AUFVX3lxTE5HdF83OXJIT2hvZUt6cFV4WWR3TDJXWG5UZW1IUzhXN21fMnU4ZGF6VjRPb0gyaHlGdWtxaFVXWUptRWF3TEl1eDBnRmozbEppWW9ueWRfcmIwWVp2cU91OXEzQ1VBV3NoU25Hbkpob25JTE9SWEYtbWRKWXpCOHRwNkgzNlBFRjYyUUsxY3dVRmVYMHNqSjhUbVZKazNfOU5NaGZ5aW9JajJiZWhiSjhDbXBqTjVuNS1sUXMtT2c?oc=5 | https://news.google.com/rss/articles/CBMijgFBVV95cUxONzdhT3NOMTZHMlN6bXZ4Q2VubTFoTkltbzd5cmxhNGJQR2tsd056NDAxTDhOaUl0Mkgwb1ZPNWF5cWtlNnZ3dkIyV2M2c0VXVmpvQnpfdW52RDJNdzFGeUxHVzR1LTA2Y1YzLVRhMVNKaVlNalRZc04tek9xenVUZG5NdGdxSXF5LW01Q2xn?oc=5 | https://www.technopat.net/2026/04/26/google-notebooklm-slayt-ozelligiyle-kisisel-verimlilik-donemi/

Top 7

1. OpenAI Privacy Filter, AI guvenliginde “yardimci katman” degil “zorunlu altyapi” sinyalini verdi. 1.5B parametreli, 128K context destekli, lokal calisabilen PII redaction modeli; training, indexing, loglama ve review pipeline’larina dogrudan gomulebilir. Kaynaklar: https://openai.com/index/introducing-openai-privacy-filter/ | https://news.google.com/rss/articles/CBMia0FVX3lxTE5Zbi1zbEx1RE9xZkEwWWk5QW82R0JvQk55SkdSajJBaGpueTc2UzM0QXd5NkJsTFZCWWthWlJsMkNYLUUxeElPd093RGpndmY1aTltellVekdxSDdOVUtBWXltb2tQbHY2Rmgw?oc=5
2. Google’da AI-generated code orani %75 seviyesine cikti iddiasi, “copilot”tan “mixed human-agent engineering”e gecisin net isareti. Buradaki kritik nokta tek basina otomasyon degil; karmasik migration islerinin insan+ajan ortakligiyla yurumesi. Kaynak: http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=69ee842b43154be094040c10856bb65c&url=https%3a%2f%2findianexpress.com%2farticle%2ftechnology%2fartificial-intelligence%2fgoogle-75-percent-ai-generated-code-sundar-pichai-10656702%2f&c=350596984028401018&mkt=tr-tr
3. 500 investment banker benchmark’i, enterprise AI’de insan-denetimsiz “last mile”in hala acik problem oldugunu gosterdi. En iyi modeller bile musteriye dogrudan gonderilecek kaliteye cikamadi; bu, verimlilik var ama tam delegasyon yok demek. Kaynak: https://the-decoder.com/500-investment-bankers-review-ai-outputs-and-find-none-ready-for-client-delivery/
4. Guney Afrika’nin taslak AI politikasini geri cekmesi, AI policy yazmanin da governance sorunu haline geldigini gosterdi. AI hakkinda policy uretirken bile kalite, tutarlilik ve uzman denetimi eksigi siyasi maliyet yaratabiliyor. Kaynaklar: https://news.google.com/rss/articles/CBMimwFBVV95cUxPa3QyQ3ltSFVYaXFBVUl1eUxXek16c0RvVEIxcm9td2RoNTdqVHVvYzRTNk8yRjc2bG1wS3J1WGpHV2ZQX0hBbVB0YXY0dkRlTmtXTkFoYUl5U09yWkVMeEJOVmV1RU5vQlBTS2lWVVRrSXZmVDh1VmpHRlJVNVZmOHBUZjhaRF83d19PQUNCLWhfVW1ka2J1NUVxZw?oc=5 | https://news.google.com/rss/articles/CBMilgFBVV95cUxPSTNYbzU4c0xUeFRKa1poT0M2a1hwNW5qajF1SEUwSHFMdEo0alFoZnlzRjQtTWZYZjFSM3hNMlA3UFZTbzZPWVdiNWZHd0I3NVJ0bHhkVmxYZmVUQVRYS2h2aVhTNUVUV1U3TnVtajlJeV9wY3JWVFZLaW56QjhFazdfX3N4VWtPYkFNX19Cc2tjdFIydUE?oc=5
5. Manitoba’nin gencler icin sosyal medya + AI kisiti hamlesi, “cocuk koruma” regülasyonunun genAI’yı da kapsayacak sekilde genisledigini gosteriyor. Bu, yakin vadede baska yargi alanlarina da sicrama potansiyeli tasiyor. Kaynak: https://news.google.com/rss/articles/CBMiwAFBVV95cUxQZDUweHNHTGJQb3d0VjVkazRvc1hKS3hsd1Vrb1N0cmo0bDBRM1NPTnlmLTZadGZ6ei1rZ1g1RWpDRVB1YWVnUWpfQmhNNEotcWdOY0J1ekZEdGkzdXI1TXg1SXZERTBMd0RaX2RvYlZ4MWxpZDZDdmxKQkIwS21xYkxHbHZrMjhCS0RIRnAwWG13b2RnMEY0enFFYmJJWjZmQXRBRE5Bb1c2eGxHN29NemVXQ19pMy1WMzQ0MXhJYUg?oc=5
6. Vizag AI data center hamlesi, compute yarısinin yeni cografyasini gosteriyor. Yatirim artik sadece ABD/AB merkezli degil; Hindistan gibi pazarlarda fiziksel kapasite kurulumu stratejik avantaj haline geliyor. Kaynak: https://news.google.com/rss/articles/CBMivgFBVV95cUxOR3RfNzlySE9ob2VLenBVeFlkd0wyV1huVGVtSFM4VzdtXzJ1OGRhelY0T29IMmh5RnVrcWhVV1lKbUVhd0xJdXgwZ0ZqM2xKaVlvbnlkX3JiMFladnFPdTlxM0NVQVdzaFNuR25KaG9uSUxPUlhGLW1kSll6Qjh0cDZIMzZQRUY2MlFLMWN3VUZlWDBzako4VG1WSmszXzlOTWhmeWlvSWoyYmVoYko4Q21wak41bjUtbFFzLU9n0gG-AUFVX3lxTE5HdF83OXJIT2hvZUt6cFV4WWR3TDJXWG5UZW1IUzhXN21fMnU4ZGF6VjRPb0gyaHlGdWtxaFVXWUptRWF3TEl1eDBnRmozbEppWW9ueWRfcmIwWVp2cU91OXEzQ1VBV3NoU25Hbkpob25JTE9SWEYtbWRKWXpCOHRwNkgzNlBFRjYyUUsxY3dVRmVYMHNqSjhUbVZKazNfOU5NaGZ5aW9JajJiZWhiSjhDbXBqTjVuNS1sUXMtT2c?oc=5
7. “AI agent deleted our production database” vakasi, agent deployment icin gercek dunyada en net kirmizi cizgilerden birini tekrar gosterdi. Agent capability artisi, rollback/approval/backup protokolleri olmadan tehlikeli. Kaynaklar: https://twitter.com/lifeof_jer/status/2048103471019434248 | https://news.ycombinator.com/item?id=47911524

KAT-1 — Industry / Piyasa

• “AI middle class” eriyor tezi, piyasada kazananlarin frontier modeller ya da cok dusuk maliyetli otomasyon katmanlari olabilecegini; aradaki genelist bilgi isinin deger baskisi altina girdigini savunuyor. Kaynak: https://news.google.com/rss/articles/CBMiYkFVX3lxTE90VzJ3aGdfRmExd09FWWk1Z1kyYVBTV2N2aUlhcXh4c0U4enA1cHZjWjdlRi1NNHBPQlNOZVFJOHhKdzRETUE2eXd4RzJCOGVmell4WXJwQUV1Q0tpajBnVGtn?oc=5
• Claude’un haftalik aktif kullanicilarinin gelir profili rakiplerinden daha yuksek, premium AI urunlerinin hangi gelir segmentlerinde daha hizli adoption gordugunu netlestiriyor. Bu, monetization ve product packaging icin onemli sinyal. Kaynak: https://the-decoder.com/survey-finds-claudes-weekly-active-users-in-the-us-skew-far-wealthier-than-any-rival-ai-assistant/
• Banker benchmark’i, enterprise ROI anlatısina soguk dus aldiriyor. AI hiz kazandiriyor ama “client-ready output” standardinda hala insan editoryasi gerekiyor; bu da seat pricing yerine workflow pricing tartismasini buyutebilir. Kaynak: https://the-decoder.com/500-investment-bankers-review-ai-outputs-and-find-none-ready-for-client-delivery/

KAT-2 — Models / Launches

• OpenAI Privacy Filter, bugunun en uygulanabilir model lansmani. “Open-weight + local + long-context + redaction” kombinasyonu, agent loglari ve memory pipeline’lari icin dogrudan kullanilabilir. Kaynaklar: https://openai.com/index/introducing-openai-privacy-filter/ | https://huggingface.co/openai/privacy-filter
• LLaDA2.0-Uni, understanding ve generation’i tek diffusion-LLM catisinda birlestirme iddiasi nedeniyle izlemeye deger. Unified multimodal stack arayisi suruyor. Kaynaklar: https://huggingface.co/inclusionAI/LLaDA2.0-Uni | https://huggingface.co/papers/2604.20796
• Kimi-K2.6 ve Qwen3.6-27B etrafindaki ilgi, acik/yarı-acik modellerde “kullanilabilirlik + deployment ergonomisi”nin ham benchmark kadar onemli hale geldigini gosteriyor. Kaynaklar: https://huggingface.co/moonshotai/Kimi-K2.6 | https://huggingface.co/Qwen/Qwen3.6-27B

KAT-3 — Agents / Products

• Google icinde AI-generated code’un %75’e cikmasi, coding agent’larin artik demo araci degil, production engineering pipeline parcasi haline geldigini gosteriyor. Kaynak: http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=69ee842b43154be094040c10856bb65c&url=https%3a%2f%2findianexpress.com%2farticle%2ftechnology%2fartificial-intelligence%2fgoogle-75-percent-ai-generated-code-sundar-pichai-10656702%2f&c=350596984028401018&mkt=tr-tr
• NotebookLM’in slayt destesi/rehber uretimi, knowledge work tarafinda “chat + note” araclarinin presentation/runtime workflow’una dogru genisledigini gosteriyor. Kaynak: https://www.technopat.net/2026/04/26/google-notebooklm-slayt-ozelligiyle-kisisel-verimlilik-donemi/
• Coachella’nin DeepMind AI ile canli eglence testleri, consumer AI’nin coding ve office disinda yaratici deneyim katmanina gecisini hizlandiriyor. Kaynak: https://news.google.com/rss/articles/CBMijgFBVV95cUxONzdhT3NOMTZHMlN6bXZ4Q2VubTFoTkltbzd5cmxhNGJQR2tsd056NDAxTDhOaUl0Mkgwb1ZPNWF5cWtlNnZ3dkIyV2M2c0VXVmpvQnpfdW52RDJNdzFGeUxHVzR1LTA2Y1YzLVRhMVNKaVlNalRZc04tek9xenVUZG5NdGdxSXF5LW01Q2xn?oc=5

KAT-4 — Research / AI Science

• Kapsamli human-in-the-loop calisma, AI sistemlerinin en guclu sonucunu insanla birlikte calistiginda verdigini; tamamen replace etmeye calistiginda kalitenin dustugunu one suruyor. Kaynak: https://news.google.com/rss/articles/CBMipgFBVV95cUxNS2JFd0VTdkptX2p3ZFJ1YkNsLW11ckdrUVFNZFVFOUNBT3VBb0JqcGRnRW5nc0hSSXpqbUxFX3AxSmhUaXZ5elJCcnhnRGtLa0piQVlUT2xzT3hfUS1vWEFsT3lITm14bVRzQzFQWXdSbUc4bTFieTE1Sk15emsybU4yVWx4aE91Z3p6Z0dJMjZzUFA4R1Utb2ZDeUhaUmFVbFcyRDZ3?oc=5
• Bone imaging’de ML kullanimi, ortopedik ve goruntu-temelli klinik arastirmada pattern discovery tarafinin derinlestigini gosteriyor. Kaynak: http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=69ee842c1dc9444c9f817bc38c200a25&url=https%3a%2f%2fmedicalxpress.com%2fnews%2f2026-04-bone-imaging-machine-uncovers-hidden.html&c=3802535024279497921&mkt=tr-tr
• Mount Sinai’nin CPAP risk tahmin modeli, medikal AI’nin “genel sohbet” degil dar, karar-destek odakli, sonuca bagli use-case’lerde daha olgun ilerledigini hatirlatiyor. Kaynak: http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=69ee842c1dc9444c9f817bc38c200a25&url=https%3a%2f%2fwww.eurekalert.org%2fnews-releases%2f1123513&c=8981021123369481719&mkt=tr-tr

KAT-5 — Security / Cyber

• Privacy Filter tipi lokal redaction katmanlari, 2026 agent stack’inde opsiyon degil temel savunma gibi gorunuyor. PII’yi makineden cikarmadan maskeleme, log/trace/memory guvenligi icin kritik. Kaynaklar: https://openai.com/index/introducing-openai-privacy-filter/ | https://huggingface.co/openai/privacy-filter
• Production DB silen AI agent vakasi, destructive action’lar icin approval, scope control, backup ve rollback’in hard gate olarak kalmasi gerektigini gosteriyor. Kaynaklar: https://twitter.com/lifeof_jer/status/2048103471019434248 | https://news.ycombinator.com/item?id=47911524
• ABD’nin Cin kaynakli AI theft uyarisi, security tartismasinin uygulama seviyesinden geopolitik model/IP koruma seviyesine tasindigini gosteriyor. Kaynak: https://news.google.com/rss/articles/CBMidkFVX3lxTE5HNXJEQ0EteEhONE04UDcteFk2MXhOVXlrTzBBRUNsX3FISUVDWFJvRDRXbXNNOUVIcjRyUkh0RkFGT3o5TDN5d0ZqT2o0SkZkLUc1d2tHX3lvMzlIZEFNZ1UtSHJoQXJUR1MzMXBEZE10RmpuaXc?oc=5

KAT-6 — Regulation / Policy

• Guney Afrika’nin taslak AI policy’yi cekmesi, “AI politikasini yayinla gitsin” evresinin kapandigini; kalite ve denetim zayifsa dogrudan geri tepebildigini gosteriyor. Kaynaklar: https://news.google.com/rss/articles/CBMimwFBVV95cUxPa3QyQ3ltSFVYaXFBVUl1eUxXek16c0RvVEIxcm9td2RoNTdqVHVvYzRTNk8yRjc2bG1wS3J1WGpHV2ZQX0hBbVB0YXY0dkRlTmtXTkFoYUl5U09yWkVMeEJOVmV1RU5vQlBTS2lWVVRrSXZmVDh1VmpHRlJVNVZmOHBUZjhaRF83d19PQUNCLWhfVW1ka2J1NUVxZw?oc=5 | https://news.google.com/rss/articles/CBMilgFBVV95cUxPSTNYbzU4c0xUeFRKa1poT0M2a1hwNW5qajF1SEUwSHFMdEo0alFoZnlzRjQtTWZYZjFSM3hNMlA3UFZTbzZPWVdiNWZHd0I3NVJ0bHhkVmxYZmVUQVRYS2h2aVhTNUVUV1U3TnVtajlJeV9wY3JWVFZLaW56QjhFazdfX3N4VWtPYkFNX19Cc2tjdFIydUE?oc=5
• Manitoba’nin gencler icin AI/sosyal medya yasagi, yas-dogrulama ve cocuk koruma dalgasinin genAI’ye dogru genislediginin guclu sinyali. Kaynak: https://news.google.com/rss/articles/CBMiwAFBVV95cUxQZDUweHNHTGJQb3d0VjVkazRvc1hKS3hsd1Vrb1N0cmo0bDBRM1NPTnlmLTZadGZ6ei1rZ1g1RWpDRVB1YWVnUWpfQmhNNEotcWdOY0J1ekZEdGkzdXI1TXg1SXZERTBMd0RaX2RvYlZ4MWxpZDZDdmxKQkIwS21xYkxHbHZrMjhCS0RIRnAwWG13b2RnMEY0enFFYmJJWjZmQXRBRE5Bb1c2eGxHN29NemVXQ19pMy1WMzQ0MXhJYUg?oc=5
• AI theft uyarilari ve cinayen compute/know-how rekabeti, regulasyonun yakinda yalniz safety degil capital flow ve technology transfer etrafinda da sertlesecegini gosteriyor. Kaynak: https://news.google.com/rss/articles/CBMidkFVX3lxTE5HNXJEQ0EteEhONE04UDcteFk2MXhOVXlrTzBBRUNsX3FISUVDWFJvRDRXbXNNOUVIcjRyUkh0RkFGT3o5TDN5d0ZqT2o0SkZkLUc1d2tHX3lvMzlIZEFNZ1UtSHJoQXJUR1MzMXBEZE10RmpuaXc?oc=5

KAT-7 — Infra / Compute

• Vizag AI data center hamlesi, Hindistan’in AI compute haritasinda yalniz model tuketicisi degil fiziksel kapasite noktasi olmak istedigini gosteriyor. Kaynak: https://news.google.com/rss/articles/CBMivgFBVV95cUxOR3RfNzlySE9ob2VLenBVeFlkd0wyV1huVGVtSFM4VzdtXzJ1OGRhelY0T29IMmh5RnVrcWhVV1lKbUVhd0xJdXgwZ0ZqM2xKaVlvbnlkX3JiMFladnFPdTlxM0NVQVdzaFNuR25KaG9uSUxPUlhGLW1kSll6Qjh0cDZIMzZQRUY2MlFLMWN3VUZlWDBzako4VG1WSmszXzlOTWhmeWlvSWoyYmVoYko4Q21wak41bjUtbFFzLU9n0gG-AUFVX3lxTE5HdF83OXJIT2hvZUt6cFV4WWR3TDJXWG5UZW1IUzhXN21fMnU4ZGF6VjRPb0gyaHlGdWtxaFVXWUptRWF3TEl1eDBnRmozbEppWW9ueWRfcmIwWVp2cU91OXEzQ1VBV3NoU25Hbkpob25JTE9SWEYtbWRKWXpCOHRwNkgzNlBFRjYyUUsxY3dVRmVYMHNqSjhUbVZKazNfOU5NaGZ5aW9JajJiZWhiSjhDbXBqTjVuNS1sUXMtT2c?oc=5
• Yerel LLM cephesinde x86 unified memory ve yeni consumer/high-end donanim beklentisi, 2026–2027 lokal inference planlarini yeniden sekillendirebilir. Kaynak: https://www.reddit.com/r/LocalLLaMA/comments/1swiylm/comparison_of_upcoming_x86_unified_memory_systems/
• Pratik inference hiz kazanclari artik repo ve driver seviyesinde geliyor. Qwen 27B INT4’te 100 tps/256K context ve Gemma speculative decoding’de 120–200 tok/s raporlari, cost-per-token hesaplarini hizla degistirebilir. Kaynaklar: https://www.reddit.com/r/LocalLLaMA/comments/1sw21op/qwen3627bint4_clocking_100_tps_with_256k_context/ | https://www.reddit.com/r/LocalLLaMA/comments/1sw782p/speculative_decoding_with_gemma431b_gemma4e2b/ | https://www.reddit.com/r/LocalLLaMA/comments/1swgwvh/mesa_pr_with_37130_llamacpp_pp_perf_gain_for/

KAT-8 — Safety / Society

• Bir arac recall surecinde AI’nin yanlis tavsiye vermesi, tuketici-yuzlu AI’da liability ve product safety’yi aniden gercek dunya sorunu haline getiriyor. Kaynak: https://news.google.com/rss/articles/CBMiygFBVV95cUxOQk5KOTR5amo5NzAwZG9aNWdqdW1RZ0JfQjhhV0dLdlJJUFozeG9tRDVTcVc1QUxVRjdmNkVZS0lLWWpXQS15R1E4V09PVTVxREx6X0hDbTFleFhiS0t3M01KZy1tMDFpd0xyaUdqS1ZCcHQ4eDByUy1LMl9qR0VPYjJKVGUxWXFZak0wOEh0alJjeFRvckpZWjYyMUhId3NWS05hOU1Gbk9Zd1c0OUFzcHNOYVQwYlh1cFBfSEZOUUlWNERyZDZmRDhn?oc=5
• “AI is coming for our aging parents” hattı, yasli kullanicilar icin AI-asistan pazarinda guven, bagimlilik ve manipülasyon risklerini one cikariyor. Kaynak: https://news.google.com/rss/articles/CBMif0FVX3lxTE5WZUFjRVphOWVidEhPRElGcmxxX25haTBkZF94bUxFREpvRU5aUUxyazh2RTlyRFVyRU9iWGh6SXp3ZVpGNHBBSEN4eHpOeVNfNkNUZXl6Vllxdjc3aEhrS0FIV1JqTkVwcVRab3RxSUxIYy1EemhfNVd4amdkT1U?oc=5
• “AI anonymity” testi ve Made-in-China video uyarisi, generative media’nin kimliklenme ve sahicilik tartismasini daha da sertlestiriyor. Kaynaklar: https://news.google.com/rss/articles/CBMitgFBVV95cUxNRUZIWlZBdE1NdWstUnZkQU01YTBDdER3MHo0bDEzR1FlcVpjLWxlcjBJbmFSMWhFMmpGRGU1TW5acDVqdS1sNDVxRU1zVk5lazRFUmEtRGJBMVRuWDRFNERNeXg5UFZJN3g2djNidGdxaHdNdmZPbGVjcWZnX00yV2xsWlVOQmt6Uy02Y0MwUVltMWpXYUVGSFlrMC1Tdnc4UnFUakQxMFJOSzE4M2E2SWpGWGRmQQ?oc=5 | https://news.google.com/rss/articles/CBMib0FVX3lxTFBrZXZUVS03VU1rTnB3V21kZjU0VDEzVVlRell3VFQ0RUpKLVBwaEVFbXVKaVB6cTlxSUVra2NHVnRRdzA0YWZaMWdqSkNQeFZuZGFsTnFaWm5QNHlYZFFxclY1ejB6MXFSTTZwNTZhUQ?oc=5

KAT-9 — Community / Meta

• GitHub’da skills kataloglarinin trend olmasi, agent ekosisteminde “prompt”tan “moduler capability package”a gecildigini gosteriyor. Kaynaklar: https://github.com/mattpocock/skills | https://github.com/ComposioHQ/awesome-codex-skills
• LabelSets gibi acik veri kalite standardi denemeleri, gelecekte dataset procurement ve audit sureclerinin daha formal hale gelebilecegine isaret ediyor. Kaynak: https://www.reddit.com/r/MachineLearning/comments/1swghah/labelsets_open_quality_standard_for_ai_training/
• OpenCode icin skill portlari ve speculative decoding repo’lari, developer toplulugunun frontier lab’leri beklemeden kendi acceleration katmanini yazdigini gosteriyor. Kaynaklar: https://www.reddit.com/r/LocalLLaMA/comments/1swf37n/opencodepowerpack_claude_code_skills_ported_to/ | https://www.reddit.com/r/MachineLearning/comments/1swfftl/speculative_decoding_implementations_eagle3/

SECURITY

• Local-first privacy filtresi, agent runtime icin yeni baseline olmali. Log, transcript, memory ve search index’e giden ham metin once lokal PII filtresinden gecmeli. Kaynaklar: https://openai.com/index/introducing-openai-privacy-filter/ | https://huggingface.co/openai/privacy-filter
• Destructive action’larda “dry-run + backup + scoped permission + insan onayi” dörtlüsü opsiyon degil zorunlu. Production DB silen ajan hikayesi bunun en acik ornegi. Kaynaklar: https://twitter.com/lifeof_jer/status/2048103471019434248 | https://news.ycombinator.com/item?id=47911524
• IP theft ve model know-how savasi, provenance/logging disiplinini sertlestirecek. Agent output’u, code diff’i ve model secimi artik governance artefakti gibi tutulmali. Kaynak: https://news.google.com/rss/articles/CBMidkFVX3lxTE5HNXJEQ0EteEhONE04UDcteFk2MXhOVXlrTzBBRUNsX3FISUVDWFJvRDRXbXNNOUVIcjRyUkh0RkFGT3o5TDN5d0ZqT2o0SkZkLUc1d2tHX3lvMzlIZEFNZ1UtSHJoQXJUR1MzMXBEZE10RmpuaXc?oc=5

REGULATION

• Policy kalitesi bizzat politika haberi haline geldi. Guney Afrika ornegi, AI strateji belgelerinde “yayin hizindan” cok “denetim kalitesi”nin siyaseten belirleyici oldugunu gosteriyor. Kaynaklar: https://news.google.com/rss/articles/CBMimwFBVV95cUxPa3QyQ3ltSFVYaXFBVUl1eUxXek16c0RvVEIxcm9td2RoNTdqVHVvYzRTNk8yRjc2bG1wS3J1WGpHV2ZQX0hBbVB0YXY0dkRlTmtXTkFoYUl5U09yWkVMeEJOVmV1RU5vQlBTS2lWVVRrSXZmVDh1VmpHRlJVNVZmOHBUZjhaRF83d19PQUNCLWhfVW1ka2J1NUVxZw?oc=5 | https://news.google.com/rss/articles/CBMilgFBVV95cUxPSTNYbzU4c0xUeFRKa1poT0M2a1hwNW5qajF1SEUwSHFMdEo0alFoZnlzRjQtTWZYZjFSM3hNMlA3UFZTbzZPWVdiNWZHd0I3NVJ0bHhkVmxYZmVUQVRYS2h2aVhTNUVUV1U3TnVtajlJeV9wY3JWVFZLaW56QjhFazdfX3N4VWtPYkFNX19Cc2tjdFIydUE?oc=5
• Youth safety regülasyonu sosyal medyadan genAI’ye dogru kayiyor. Manitoba bugun uctaki vaka gibi gorunse de “children + AI” basliginda yeni normlarin habercisi olabilir. Kaynak: https://news.google.com/rss/articles/CBMiwAFBVV95cUxQZDUweHNHTGJQb3d0VjVkazRvc1hKS3hsd1Vrb1N0cmo0bDBRM1NPTnlmLTZadGZ6ei1rZ1g1RWpDRVB1YWVnUWpfQmhNNEotcWdOY0J1ekZEdGkzdXI1TXg1SXZERTBMd0RaX2RvYlZ4MWxpZDZDdmxKQkIwS21xYkxHbHZrMjhCS0RIRnAwWG13b2RnMEY0enFFYmJJWjZmQXRBRE5Bb1c2eGxHN29NemVXQ19pMy1WMzQ0MXhJYUg?oc=5
• Geopolitik AI regülasyonu “safety”nin yanina “sermaye ve teknoloji akisi” boyutunu ekliyor. ABD-Cin AI theft warnings, yatirim ve bilgi transferinde daha dar kapilarin habercisi. Kaynak: https://news.google.com/rss/articles/CBMidkFVX3lxTE5HNXJEQ0EteEhONE04UDcteFk2MXhOVXlrTzBBRUNsX3FISUVDWFJvRDRXbXNNOUVIcjRyUkh0RkFGT3o5TDN5d0ZqT2o0SkZkLUc1d2tHX3lvMzlIZEFNZ1UtSHJoQXJUR1MzMXBEZE10RmpuaXc?oc=5

AI-SCIENCE

• Bugunun daha guclu bilimsel sinyali, autonomous genius degil structured assistance. Human-in-loop calisma, banker benchmark ve klinik ML haberleri ayni yone bakiyor: dar, denetimli yardim daha iyi calisiyor. Kaynaklar: https://news.google.com/rss/articles/CBMipgFBVV95cUxNS2JFd0VTdkptX2p3ZFJ1YkNsLW11ckdrUVFNZFVFOUNBT3VBb0JqcGRnRW5nc0hSSXpqbUxFX3AxSmhUaXZ5elJCcnhnRGtLa0piQVlUT2xzT3hfUS1vWEFsT3lITm14bVRzQzFQWXdSbUc4bTFieTE1Sk15emsybU4yVWx4aE91Z3p6Z0dJMjZzUFA4R1Utb2ZDeUhaUmFVbFcyRDZ3?oc=5 | https://the-decoder.com/500-investment-bankers-review-ai-outputs-and-find-none-ready-for-client-delivery/ | http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=69ee842c1dc9444c9f817bc38c200a25&url=https%3a%2f%2fwww.eurekalert.org%2fnews-releases%2f1123513&c=8981021123369481719&mkt=tr-tr
• Medikal ML cephesi, dar domain’de olculen kazanc uretmeye devam ediyor. Bone imaging ve CPAP risk modelleme haberleri, klinikte hedefli yardimci modellerin hala en saglam AI-science rotasi oldugunu destekliyor. Kaynaklar: http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=69ee842c1dc9444c9f817bc38c200a25&url=https%3a%2f%2fmedicalxpress.com%2fnews%2f2026-04-bone-imaging-machine-uncovers-hidden.html&c=3802535024279497921&mkt=tr-tr | http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=69ee842c1dc9444c9f817bc38c200a25&url=https%3a%2f%2fwww.eurekalert.org%2fnews-releases%2f1123513&c=8981021123369481719&mkt=tr-tr
• Unified multimodal model arayisi suruyor. LLaDA2.0-Uni gibi cikislar, “tek model hem anlasin hem uretsin” hedefine dogru yeni denemeleri canli tutuyor. Kaynaklar: https://huggingface.co/inclusionAI/LLaDA2.0-Uni | https://huggingface.co/papers/2604.20796

INFRA

• Regional compute expansion devam ediyor: Vizag, AI’nin cografi olarak daha daginik altyapi evresine girdigini gosteriyor. Kaynak: https://news.google.com/rss/articles/CBMivgFBVV95cUxOR3RfNzlySE9ob2VLenBVeFlkd0wyV1huVGVtSFM4VzdtXzJ1OGRhelY0T29IMmh5RnVrcWhVV1lKbUVhd0xJdXgwZ0ZqM2xKaVlvbnlkX3JiMFladnFPdTlxM0NVQVdzaFNuR25KaG9uSUxPUlhGLW1kSll6Qjh0cDZIMzZQRUY2MlFLMWN3VUZlWDBzako4VG1WSmszXzlOTWhmeWlvSWoyYmVoYko4Q21wak41bjUtbFFzLU9n0gG-AUFVX3lxTE5HdF83OXJIT2hvZUt6cFV4WWR3TDJXWG5UZW1IUzhXN21fMnU4ZGF6VjRPb0gyaHlGdWtxaFVXWUptRWF3TEl1eDBnRmozbEppWW9ueWRfcmIwWVp2cU91OXEzQ1VBV3NoU25Hbkpob25JTE9SWEYtbWRKWXpCOHRwNkgzNlBFRjYyUUsxY3dVRmVYMHNqSjhUbVZKazNfOU5NaGZ5aW9JajJiZWhiSjhDbXBqTjVuNS1sUXMtT2c?oc=5
• Local inference economics hizla iyilesiyor. 27B-31B civari modellerde quantization, speculative decoding ve driver optimizasyonu pratik kulanimi anlamli sekilde ileri itiyor. Kaynaklar: https://www.reddit.com/r/LocalLLaMA/comments/1sw21op/qwen3627bint4_clocking_100_tps_with_256k_context/ | https://www.reddit.com/r/LocalLLaMA/comments/1sw782p/speculative_decoding_with_gemma431b_gemma4e2b/ | https://www.reddit.com/r/LocalLLaMA/comments/1swgwvh/mesa_pr_with_37130_llamacpp_pp_perf_gain_for/
• Unified memory beklentisi, lokal agent donanimi icin oyun degistirici olabilir. PC/server siniri bulanirsa agent deployment cost curve yeniden yazilir. Kaynak: https://www.reddit.com/r/LocalLLaMA/comments/1swiylm/comparison_of_upcoming_x86_unified_memory_systems/

SAFETY

• Consumer AI’de yanlis recall tavsiyesi, “hallucination”i hukuki ve fiziksel risk kategorisine tasiyor. Kaynak: https://news.google.com/rss/articles/CBMiygFBVV95cUxOQk5KOTR5amo5NzAwZG9aNWdqdW1RZ0JfQjhhV0dLdlJJUFozeG9tRDVTcVc1QUxVRjdmNkVZS0lLWWpXQS15R1E4V09PVTVxREx6X0hDbTFleFhiS0t3M01KZy1tMDFpd0xyaUdqS1ZCcHQ4eDByUy1LMl9qR0VPYjJKVGUxWXFZak0wOEh0alJjeFRvckpZWjYyMUhId3NWS05hOU1Gbk9Zd1c0OUFzcHNOYVQwYlh1cFBfSEZOUUlWNERyZDZmRDhn?oc=5
• Aging parents gibi hassas kullanici gruplari, AI asistanlarinda manipülasyon ve asiri guven riskini buyutuyor. Kaynak: https://news.google.com/rss/articles/CBMif0FVX3lxTE5WZUFjRVphOWVidEhPRElGcmxxX25haTBkZF94bUxFREpvRU5aUUxyazh2RTlyRFVyRU9iWGh6SXp3ZVpGNHBBSEN4eHpOeVNfNkNUZXl6Vllxdjc3aEhrS0FIV1JqTkVwcVRab3RxSUxIYy1EemhfNVd4amdkT1U?oc=5
• Anonimlik ve orijin sorunu buyuyor. Kim urettigi belli olmayan video ve AI yardimli deanonymization testleri, provenance katmanini zorunlu kilabilir. Kaynaklar: https://news.google.com/rss/articles/CBMitgFBVV95cUxNRUZIWlZBdE1NdWstUnZkQU01YTBDdER3MHo0bDEzR1FlcVpjLWxlcjBJbmFSMWhFMmpGRGU1TW5acDVqdS1sNDVxRU1zVk5lazRFUmEtRGJBMVRuWDRFNERNeXg5UFZJN3g2djNidGdxaHdNdmZPbGVjcWZnX00yV2xsWlVOQmt6Uy02Y0MwUVltMWpXYUVGSFlrMC1Tdnc4UnFUakQxMFJOSzE4M2E2SWpGWGRmQQ?oc=5 | https://news.google.com/rss/articles/CBMib0FVX3lxTFBrZXZUVS03VU1rTnB3V21kZjU0VDEzVVlRell3VFQ0RUpKLVBwaEVFbXVKaVB6cTlxSUVra2NHVnRRdzA0YWZaMWdqSkNQeFZuZGFsTnFaWm5QNHlYZFFxclY1ejB6MXFSTTZwNTZhUQ?oc=5

WATCHLIST

• Privacy Filter’in gercek dunya precision/recall dengesi: benchmark basarisi prod pipeline’da false positive / false negative maliyetine nasil donusecek? Kaynaklar: https://openai.com/index/introducing-openai-privacy-filter/ | https://huggingface.co/openai/privacy-filter
• Google’daki %75 AI code orani, defect rate ve review yukunu nasil etkiliyor? Verim artik tek metric olmamali. Kaynak: http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=69ee842b43154be094040c10856bb65c&url=https%3a%2f%2findianexpress.com%2farticle%2ftechnology%2fartificial-intelligence%2fgoogle-75-percent-ai-generated-code-sundar-pichai-10656702%2f&c=350596984028401018&mkt=tr-tr
• Manitoba benzeri youth-AI kisitlari yayilirsa, genAI urunlerinde yas, parental control ve default-safety konfigürasyonlari baski altina girecek. Kaynak: https://news.google.com/rss/articles/CBMiwAFBVV95cUxQZDUweHNHTGJQb3d0VjVkazRvc1hKS3hsd1Vrb1N0cmo0bDBRM1NPTnlmLTZadGZ6ei1rZ1g1RWpDRVB1YWVnUWpfQmhNNEotcWdOY0J1ekZEdGkzdXI1TXg1SXZERTBMd0RaX2RvYlZ4MWxpZDZDdmxKQkIwS21xYkxHbHZrMjhCS0RIRnAwWG13b2RnMEY0enFFYmJJWjZmQXRBRE5Bb1c2eGxHN29NemVXQ19pMy1WMzQ0MXhJYUg?oc=5
• Investment banking benchmark gibi domain-specific eval’ler diger bilgi islerine sicrarsa, “general benchmark” odakli model pazarlamasi daha hizli sorgulanacak. Kaynak: https://the-decoder.com/500-investment-bankers-review-ai-outputs-and-find-none-ready-for-client-delivery/
• Local inference stack’inde unified memory + speculative decoding + driver gains, 2026’nin ikinci yarisinda local-agent economics’i sert sekilde degistirebilir. Kaynaklar: https://www.reddit.com/r/LocalLLaMA/comments/1swiylm/comparison_of_upcoming_x86_unified_memory_systems/ | https://www.reddit.com/r/LocalLLaMA/comments/1sw782p/speculative_decoding_with_gemma431b_gemma4e2b/ | https://www.reddit.com/r/LocalLLaMA/comments/1swgwvh/mesa_pr_with_37130_llamacpp_pp_perf_gain_for/

TRENDS

• Trend 1 — “Assist, don’t replace” gucleniyor. Human-in-loop study + banker eval + Google mixed-team coding beraber okununca tam otonomi yerine hibrit workflow’un onde oldugu goruluyor. Kaynaklar: https://news.google.com/rss/articles/CBMipgFBVV95cUxNS2JFd0VTdkptX2p3ZFJ1YkNsLW11ckdrUVFNZFVFOUNBT3VBb0JqcGRnRW5nc0hSSXpqbUxFX3AxSmhUaXZ5elJCcnhnRGtLa0piQVlUT2xzT3hfUS1vWEFsT3lITm14bVRzQzFQWXdSbUc4bTFieTE1Sk15emsybU4yVWx4aE91Z3p6Z0dJMjZzUFA4R1Utb2ZDeUhaUmFVbFcyRDZ3?oc=5 | https://the-decoder.com/500-investment-bankers-review-ai-outputs-and-find-none-ready-for-client-delivery/ | http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=69ee842b43154be094040c10856bb65c&url=https%3a%2f%2findianexpress.com%2farticle%2ftechnology%2fartificial-intelligence%2fgoogle-75-percent-ai-generated-code-sundar-pichai-10656702%2f&c=350596984028401018&mkt=tr-tr
• Trend 2 — Governance upstream’e kayiyor. Policy draft kalitesi, youth restrictions ve anonymity tartismasi; guvenlik filtresi kadar yonetim kalitesinin de urun parcasi oldugunu gosteriyor. Kaynaklar: https://news.google.com/rss/articles/CBMimwFBVV95cUxPa3QyQ3ltSFVYaXFBVUl1eUxXek16c0RvVEIxcm9td2RoNTdqVHVvYzRTNk8yRjc2bG1wS3J1WGpHV2ZQX0hBbVB0YXY0dkRlTmtXTkFoYUl5U09yWkVMeEJOVmV1RU5vQlBTS2lWVVRrSXZmVDh1VmpHRlJVNVZmOHBUZjhaRF83d19PQUNCLWhfVW1ka2J1NUVxZw?oc=5 | https://news.google.com/rss/articles/CBMiwAFBVV95cUxQZDUweHNHTGJQb3d0VjVkazRvc1hKS3hsd1Vrb1N0cmo0bDBRM1NPTnlmLTZadGZ6ei1rZ1g1RWpDRVB1YWVnUWpfQmhNNEotcWdOY0J1ekZEdGkzdXI1TXg1SXZERTBMd0RaX2RvYlZ4MWxpZDZDdmxKQkIwS21xYkxHbHZrMjhCS0RIRnAwWG13b2RnMEY0enFFYmJJWjZmQXRBRE5Bb1c2eGxHN29NemVXQ19pMy1WMzQ0MXhJYUg?oc=5 | https://news.google.com/rss/articles/CBMitgFBVV95cUxNRUZIWlZBdE1NdWstUnZkQU01YTBDdER3MHo0bDEzR1FlcVpjLWxlcjBJbmFSMWhFMmpGRGU1TW5acDVqdS1sNDVxRU1zVk5lazRFUmEtRGJBMVRuWDRFNERNeXg5UFZJN3g2djNidGdxaHdNdmZPbGVjcWZnX00yV2xsWlVOQmt6Uy02Y0MwUVltMWpXYUVGSFlrMC1Tdnc4UnFUakQxMFJOSzE4M2E2SWpGWGRmQQ?oc=5
• Trend 3 — Applied AI paketleniyor. Privacy filter, NotebookLM slides ve entertainment AI kullanimi; model capability’nin belirli workflow paketlerine donustugunu gosteriyor. Kaynaklar: https://openai.com/index/introducing-openai-privacy-filter/ | https://www.technopat.net/2026/04/26/google-notebooklm-slayt-ozelligiyle-kisisel-verimlilik-donemi/ | https://news.google.com/rss/articles/CBMijgFBVV95cUxONzdhT3NOMTZHMlN6bXZ4Q2VubTFoTkltbzd5cmxhNGJQR2tsd056NDAxTDhOaUl0Mkgwb1ZPNWF5cWtlNnZ3dkIyV2M2c0VXVmpvQnpfdW52RDJNdzFGeUxHVzR1LTA2Y1YzLVRhMVNKaVlNalRZc04tek9xenVUZG5NdGdxSXF5LW01Q2xn?oc=5
• Trend 4 — Local/open developer stack olgunlasiyor. Skills kataloglari, OpenCode portlari ve inference hiz kazanclari toplulugun kendi acceleration katmanini kurdugunu gosteriyor. Kaynaklar: https://github.com/mattpocock/skills | https://github.com/ComposioHQ/awesome-codex-skills | https://www.reddit.com/r/LocalLLaMA/comments/1swf37n/opencodepowerpack_claude_code_skills_ported_to/ | https://www.reddit.com/r/LocalLLaMA/comments/1sw21op/qwen3627bint4_clocking_100_tps_with_256k_context/

CikCik Paketi

• Tweet 1: AI’nin 2026 gercegi: isleri tamamen devralmiyor, is akisini yeniden parcaliyor. Google “%75 AI-generated code” diyor; ama 500 banker eval’inde tek bir model cikisi musteriye dogrudan gitmeye hazir degil. Hibrit donem resmen basladi. Kaynaklar: http://www.bing.com/news/apiclick.aspx?ref=FexRss&aid=&tid=69ee842b43154be094040c10856bb65c&url=https%3a%2f%2findianexpress.com%2farticle%2ftechnology%2fartificial-intelligence%2fgoogle-75-percent-ai-generated-code-sundar-pichai-10656702%2f&c=350596984028401018&mkt=tr-tr | https://the-decoder.com/500-investment-bankers-review-ai-outputs-and-find-none-ready-for-client-delivery/
• Tweet 2: OpenAI Privacy Filter bence bugunun en kullanilabilir AI lansmani. Sebep: hype degil altyapi. Lokal PII redaction, 128K context, training/log/memory pipeline’ina direkt girer. Agent guvenligi boyle seylerle gerceklesiyor. Kaynaklar: https://openai.com/index/introducing-openai-privacy-filter/ | https://huggingface.co/openai/privacy-filter
• Tweet 3: Guney Afrika’nin taslak AI politikasini geri cekmesi onemli bir sinyal: AI hakkinda policy yazmak bile governance kalitesi testi haline geldi. Hızli yayinla-gec devri bitiyor. Kaynak: https://news.google.com/rss/articles/CBMimwFBVV95cUxPa3QyQ3ltSFVYaXFBVUl1eUxXek16c0RvVEIxcm9td2RoNTdqVHVvYzRTNk8yRjc2bG1wS3J1WGpHV2ZQX0hBbVB0YXY0dkRlTmtXTkFoYUl5U09yWkVMeEJOVmV1RU5vQlBTS2lWVVRrSXZmVDh1VmpHRlJVNVZmOHBUZjhaRF83d19PQUNCLWhfVW1ka2J1NUVxZw?oc=5
• Tweet 4: Manitoba’nin gencler icin sosyal medya + AI kisiti, cocuk koruma regülasyonunun genAI’ya dogru genisledigini gosteriyor. Bu tekil olay degil, bence yeni policy dalgasinin fragmani. Kaynak: https://news.google.com/rss/articles/CBMiwAFBVV95cUxQZDUweHNHTGJQb3d0VjVkazRvc1hKS3hsd1Vrb1N0cmo0bDBRM1NPTnlmLTZadGZ6ei1rZ1g1RWpDRVB1YWVnUWpfQmhNNEotcWdOY0J1ekZEdGkzdXI1TXg1SXZERTBMd0RaX2RvYlZ4MWxpZDZDdmxKQkIwS21xYkxHbHZrMjhCS0RIRnAwWG13b2RnMEY0enFFYmJJWjZmQXRBRE5Bb1c2eGxHN29NemVXQ19pMy1WMzQ0MXhJYUg?oc=5
• Tweet 5: “AI agent deleted our production database” hikayesi tek cumlede 2026 dersini veriyor: capability artisi ≠ operational maturity. Backup, approval, rollback yoksa agent degil risk amplifikatörü kuruyorsun. Kaynaklar: https://twitter.com/lifeof_jer/status/2048103471019434248 | https://news.ycombinator.com/item?id=47911524
• Thread fikri: “Assist vs Replace: 2026’da AI’nin gerçek bottleneck’i model zekasi degil, insan onayi gerektiren son kilometre.” Ornekler: banker eval, recall hatasi, production DB silme, privacy filtering. Kaynaklar: https://the-decoder.com/500-investment-bankers-review-ai-outputs-and-find-none-ready-for-client-delivery/ | https://news.google.com/rss/articles/CBMiygFBVV95cUxOQk5KOTR5amo5NzAwZG9aNWdqdW1RZ0JfQjhhV0dLdlJJUFozeG9tRDVTcVc1QUxVRjdmNkVZS0lLWWpXQS15R1E4V09PVTVxREx6X0hDbTFleFhiS0t3M01KZy1tMDFpd0xyaUdqS1ZCcHQ4eDByUy1LMl9qR0VPYjJKVGUxWXFZak0wOEh0alJjeFRvckpZWjYyMUhId3NWS05hOU1Gbk9Zd1c0OUFzcHNOYVQwYlh1cFBfSEZOUUlWNERyZDZmRDhn?oc=5 | https://openai.com/index/introducing-openai-privacy-filter/

Oracle Self-Improvement Sinyalleri

• Memory ve log pipeline’lari icin lokal PII redaction on-gate eklenmeli. Privacy Filter benzeri katman olmadan uzun sureli hafiza ve transcript search, gereksiz veri riski tasiyor. Kaynaklar: https://openai.com/index/introducing-openai-privacy-filter/ | https://huggingface.co/openai/privacy-filter
• Destructive tool-call’larda “backup/rollback hazir degilse dur” kurali sertlestirilmeli. Production DB silen agent vakasi, izin/niyet dogrulamanin tek basina yetmedigini gosteriyor. Kaynaklar: https://twitter.com/lifeof_jer/status/2048103471019434248 | https://news.ycombinator.com/item?id=47911524
• Business-critical output’larda human-review kapisi korunmali. Banker benchmark ve human-in-loop calisma, son kilometrede insan denetiminin hala kalite carpani oldugunu netlestiriyor. Kaynaklar: https://the-decoder.com/500-investment-bankers-review-ai-outputs-and-find-none-ready-for-client-delivery/ | https://news.google.com/rss/articles/CBMipgFBVV95cUxNS2JFd0VTdkptX2p3ZFJ1YkNsLW11ckdrUVFNZFVFOUNBT3VBb0JqcGRnRW5nc0hSSXpqbUxFX3AxSmhUaXZ5elJCcnhnRGtLa0piQVlUT2xzT3hfUS1vWEFsT3lITm14bVRzQzFQWXdSbUc4bTFieTE1Sk15emsybU4yVWx4aE91Z3p6Z0dJMjZzUFA4R1Utb2ZDeUhaUmFVbFcyRDZ3?oc=5
• Policy/strategy haberlerinde birincil ve ikincil kaynak ayrimi daha sert yapilmali. SA policy withdrawal ornegi, policy kalitesinin bile politik olay oldugunu gosteriyor; aggregatorden kesin hukum cikarmak riskli. Kaynaklar: https://news.google.com/rss/articles/CBMimwFBVV95cUxPa3QyQ3ltSFVYaXFBVUl1eUxXek16c0RvVEIxcm9td2RoNTdqVHVvYzRTNk8yRjc2bG1wS3J1WGpHV2ZQX0hBbVB0YXY0dkRlTmtXTkFoYUl5U09yWkVMeEJOVmV1RU5vQlBTS2lWVVRrSXZmVDh1VmpHRlJVNVZmOHBUZjhaRF83d19PQUNCLWhfVW1ka2J1NUVxZw?oc=5 | https://news.google.com/rss/articles/CBMilgFBVV95cUxPSTNYbzU4c0xUeFRKa1poT0M2a1hwNW5qajF1SEUwSHFMdEo0alFoZnlzRjQtTWZYZjFSM3hNMlA3UFZTbzZPWVdiNWZHd0I3NVJ0bHhkVmxYZmVUQVRYS2h2aVhTNUVUV1U3TnVtajlJeV9wY3JWVFZLaW56QjhFazdfX3N4VWtPYkFNX19Cc2tjdFIydUE?oc=5
• Open tool ecosystem takibi bir yetenek kaynagi haline gelmeli. Skills kataloglari, inference repo’lari ve acik standardlar tekrar eden isleri skill/tool’a donusturmek icin erken sinyal veriyor. Kaynaklar: https://github.com/mattpocock/skills | https://github.com/ComposioHQ/awesome-codex-skills | https://www.reddit.com/r/MachineLearning/comments/1swghah/labelsets_open_quality_standard_for_ai_training/
• Kullanici segmentasyonu stratejik onem tasiyor. Claude’un daha varlikli kullanici kitlesi ve “AI middle class” anlatisi, herkese ayni paket yerine segment-bazli urunleme dusunmenin gerektigini gosteriyor. Kaynaklar: https://the-decoder.com/survey-finds-claudes-weekly-active-users-in-the-us-skew-far-wealthier-than-any-rival-ai-assistant/ | https://news.google.com/rss/articles/CBMiYkFVX3lxTE90VzJ3aGdfRmExd09FWWk1Z1kyYVBTV2N2aUlhcXh4c0U4enA1cHZjWjdlRi1NNHBPQlNOZVFJOHhKdzRETUE2eXd4RzJCOGVmell4WXJwQUV1Q0tpajBnVGtn?oc=5

Kaynak Ozeti

• Birincil urun/lansman kaynaklari, bugun en guvenilir uygulama sinyallerini verdi: Privacy Filter ve OpenAI’nin acik modeli bunlarin basi cekti. Kaynaklar: https://openai.com/index/introducing-openai-privacy-filter/ | https://huggingface.co/openai/privacy-filter
• The Decoder ve benzeri analiz kaynaklari, enterprise-ready kalite tavani ve gelir segmentasyonu gibi “ham benchmark disi” sinyalleri yakalamada gucluydu. Kaynaklar: https://the-decoder.com/500-investment-bankers-review-ai-outputs-and-find-none-ready-for-client-delivery/ | https://the-decoder.com/survey-finds-claudes-weekly-active-users-in-the-us-skew-far-wealthier-than-any-rival-ai-assistant/
• Google News RSS katmani, policy, safety ve bolgesel infra haberlerinde genis coverage sagladi; canonical kaynak cozumu gereken maddelerde iddialar daha temkinli kullanildi. Kaynaklar: https://news.google.com/rss/articles/CBMimwFBVV95cUxPa3QyQ3ltSFVYaXFBVUl1eUxXek16c0RvVEIxcm9td2RoNTdqVHVvYzRTNk8yRjc2bG1wS3J1WGpHV2ZQX0hBbVB0YXY0dkRlTmtXTkFoYUl5U09yWkVMeEJOVmV1RU5vQlBTS2lWVVRrSXZmVDh1VmpHRlJVNVZmOHBUZjhaRF83d19PQUNCLWhfVW1ka2J1NUVxZw?oc=5 | https://news.google.com/rss/articles/CBMiwAFBVV95cUxQZDUweHNHTGJQb3d0VjVkazRvc1hKS3hsd1Vrb1N0cmo0bDBRM1NPTnlmLTZadGZ6ei1rZ1g1RWpDRVB1YWVnUWpfQmhNNEotcWdOY0J1ekZEdGkzdXI1TXg1SXZERTBMd0RaX2RvYlZ4MWxpZDZDdmxKQkIwS21xYkxHbHZrMjhCS0RIRnAwWG13b2RnMEY0enFFYmJJWjZmQXRBRE5Bb1c2eGxHN29NemVXQ19pMy1WMzQ0MXhJYUg?oc=5 | https://news.google.com/rss/articles/CBMivgFBVV95cUxOR3RfNzlySE9ob2VLenBVeFlkd0wyV1huVGVtSFM4VzdtXzJ1OGRhelY0T29IMmh5RnVrcWhVV1lKbUVhd0xJdXgwZ0ZqM2xKaVlvbnlkX3JiMFladnFPdTlxM0NVQVdzaFNuR25KaG9uSUxPUlhGLW1kSll6Qjh0cDZIMzZQRUY2MlFLMWN3VUZlWDBzako4VG1WSmszXzlOTWhmeWlvSWoyYmVoYko4Q21wak41bjUtbFFzLU9n0gG-AUFVX3lxTE5HdF83OXJIT2hvZUt6cFV4WWR3TDJXWG5UZW1IUzhXN21fMnU4ZGF6VjRPb0gyaHlGdWtxaFVXWUptRWF3TEl1eDBnRmozbEppWW9ueWRfcmIwWVp2cU91OXEzQ1VBV3NoU25Hbkpob25JTE9SWEYtbWRKWXpCOHRwNkgzNlBFRjYyUUsxY3dVRmVYMHNqSjhUbVZKazNfOU5NaGZ5aW9JajJiZWhiSjhDbXBqTjVuNS1sUXMtT2c?oc=5
• HN/Reddit/LocalLLaMA/GitHub katmani, lokal inference, driver kazanclari, skills ekosistemi ve sahadaki agent problemlerini gormek icin yuksek erken-sinyal degeri sundu; ancak prod-iddialarda teyit ihtiyaci korunmali. Kaynaklar: https://news.ycombinator.com/item?id=47911524 | https://www.reddit.com/r/LocalLLaMA/comments/1sw21op/qwen3627bint4_clocking_100_tps_with_256k_context/ | https://www.reddit.com/r/LocalLLaMA/comments/1swgwvh/mesa_pr_with_37130_llamacpp_pp_perf_gain_for/ | https://github.com/mattpocock/skills