n8n vs Make.com vs Zapier: The Ultimate AI Automation Comparison
Three automation platforms, three different philosophies. We built the same 10 AI workflows on each platform to find the definitive winner for different use cases.
https://wowhow.cloud/blogs/n8n-vs-make-vs-zapier-ultimate-ai-automation-comparison
Kunal Nayyar turns 45, reveals his birthday wish: Make this world a more loving place #KunalNayyar #Make #socialnewsxyz
Mumbai, May 1 (SocialNews.XYZ) Actor Kunal Nayyar, who is popular for his role in the American TV show “The Big Bang Theory”, has turned 45 and hopes that when his time comes, he makes this... - Social News XYZ
new to me "GNU #Make: Rules with Grouped Targets" https://www.gnu.org/software/make/manual/html_node/Multiple-Targets.html#Rules-with-Grouped-Targets
" you have a recipe that generates multiple files from a single invocation, you can express that relationship by declaring your rule to use grouped targets"
Make AI Agents : créez votre assistant email en 20 min
Construisez un agent IA qui lit vos emails, répond aux questions fréquentes et escalade le reste sur Slack. 20 minutes, zéro code, dès 9 €/mois.
#IA #IntelligenceArtificielle #make #agentsia #automatisationia #tutorielia
記者の社会責任
人々が貴方達記者の方々に求めてるのは
Скажу одразу і чітко
https://www.deviantart.com/poison-raika/art/Kisha-no-Shakai-Sekinin-1250025674
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#journalist #social #responsibility #make #clear #mechanically #question #zombie #inevitable #other #everyone #already #sick #people #expect #just #deliver #information #extract #information #interview #have #interest #point #intelligent
記者の社会責任
人々が貴方達記者の方々に求めてるのは
Скажу одразу і чітко
https://www.deviantart.com/poison-raika/art/Kisha-no-Shakai-Sekinin-1250025674
<>
#journalist #social #responsibility #make #clear #mechanically #question #zombie #inevitable #other #everyone #already #sick #people #expect #just #deliver #information #extract #information #interview #have #interest #point #intelligent
Zum heutigen #toolsday stellen wir euch **just** vor – einen modernen Command Runner für die Kommandozeile. Anders als Make ist just zur ausführung von kommandos gedacht. Dabei unterstützt #just Autovervollständigung, Argumente, Umgebungsvariablen und verschiedene Shell-Sprachen. Leichtgewichtig, ohne Dependencies und plattformübergreifend.
記者の社会責任
人々が貴方達記者の方々に求めてるのは
Скажу одразу і чітко
https://note.com/poison_raika/n/nb2c1df9e53b6
<>
#journalist #social #responsibility #make #clear #mechanically #question #zombie #inevitable #other #everyone #already #sick #people #expect #just #deliver #information #extract #information #interview #have #interest #point #intelligent
記者の成すべき仕事又は、果たすべき社会的責任は何ですか？ 最初にハッキリ申し上げます、ゾンビの如く機械的に同じ質問を繰り返し行う事では有りません。他社の記者の質問が被るのは仕方ないですが、誰もが答えを解り切ってる又は、耳にタコが出来程聞き飽きてる事を、揃いに揃って全員で繰り返し聞く事では無い。 人々が貴方達記者の方々に求めてるのはたった一本、二本の質問を揃うに揃って行う事では全く有りません。 社会が貴方方に求めてるのは、知りたい情報を届ける事、感じた疑問を答える事。取材対象者からそうした情報を引き出すのが貴方方が果たすべき社会責任です。 人々が何を知りたいのかを知り、如何な疑
記者の社会責任
人々が貴方達記者の方々に求めてるのは
Скажу одразу і чітко
https://note.com/poison_raika/n/nb2c1df9e53b6
<>
#journalist #social #responsibility #make #clear #mechanically #question #zombie #inevitable #other #everyone #already #sick #people #expect #just #deliver #information #extract #information #interview #have #interest #point #intelligent
記者の成すべき仕事又は、果たすべき社会的責任は何ですか？ 最初にハッキリ申し上げます、ゾンビの如く機械的に同じ質問を繰り返し行う事では有りません。他社の記者の質問が被るのは仕方ないですが、誰もが答えを解り切ってる又は、耳にタコが出来程聞き飽きてる事を、揃いに揃って全員で繰り返し聞く事では無い。 人々が貴方達記者の方々に求めてるのはたった一本、二本の質問を揃うに揃って行う事では全く有りません。 社会が貴方方に求めてるのは、知りたい情報を届ける事、感じた疑問を答える事。取材対象者からそうした情報を引き出すのが貴方方が果たすべき社会責任です。 人々が何を知りたいのかを知り、如何な疑
RT @FlorianGallwitz: Der ganze Podcast ist interessant, wenn man sich für die Struktur der "Token-Ökonomie" interessiert, in der es darum geht, Energie möglichst effizient in KI-Tokens ("Intelligenz") zu verwandeln. Energie ist für Huang der Flaschenhals, der am wenigsten schnell zu beseitigen ist. Dwarkesh Patel (@dwarkesh_sp) Distilled recap of the back-and-forth with Jensen on export controls: Dwarkesh: Wouldn’t selling Nvidia chips to China enable them to train models like Claude Mythos with cyber offensive capabilities that would be threats to American companies and national security? Jensen: First of all, Mythos was trained on fairly mundane capacity and a fairly mundane amount of it by an extraordinary company. The amount of capacity and the type of compute it was trained on is abundantly available in China. Dwarkesh: With that, could they eventually train a model like Mythos? Yes. But the question is, because we have more FLOPs, American labs are able to get to this level of capabilities first. Furthermore, even if they trained a model like this, the ability to deploy it at scale matters. If you had a cyber hacker, it's much more dangerous if they have a million of them versus a thousand of them. Jensen: Your premise is just wrong. The fact of the matter is their AI development is going just fine. The best AI researchers in the world, because they are limited in compute, also come up with extremely smart algorithms. DeepSeek is not an inconsequential advance. The day that DeepSeek comes out on Huawei first, that is a horrible outcome for our nation. Dwarkesh: Currently, you can have a m…
mehr auf Arint.info
#Anthropic #China #Claude #DeepSeek #go #make #nitter #opensource #rest #scale #Tesla #things #UnitedStates #arint_info
<p>RT @FlorianGallwitz: Der ganze Podcast ist interessant, wenn man sich für die Struktur der "Token-Ökonomie" interessiert, in der es darum geht, Energie möglichst effizient in KI-Tokens ("Intelligenz") zu verwandeln. Energie ist für Huang der Flaschenhals, der am wenigsten schnell zu beseitigen ist. Dwarkesh Patel (@dwarkesh_sp) Distilled recap of the back-and-forth with Jensen on export controls: Dwarkesh: Wouldn’t selling Nvidia chips to China enable them to train models like Claude Mythos with cyber offensive capabilities that would be threats to American companies and national security? Jensen: First of all, Mythos was trained on fairly mundane capacity and a fairly mundane amount of it by an extraordinary company. The amount of capacity and the type of compute it was trained on is abundantly available in China. Dwarkesh: With that, could they eventually train a model like Mythos? Yes. But the question is, because we have more FLOPs, American labs are able to get to this level of capabilities first. Furthermore, even if they trained a model like this, the ability to deploy it at scale matters. If you had a cyber hacker, it's much more dangerous if they have a million of them versus a thousand of them. Jensen: Your premise is just wrong. The fact of the matter is their AI development is going just fine. The best AI researchers in the world, because they are limited in compute, also come up with extremely smart algorithms. DeepSeek is not an inconsequential advance. The day that DeepSeek comes out on Huawei first, that is a horrible outcome for our nation. Dwarkesh: Currently, you can have a m…</p> <p><a href="https://arint.info/@Arint/116477504486275928">mehr</a> auf <a href="https://arint.info/">Arint.info</a></p> <p>#Anthropic #China #Claude #DeepSeek #go #make #nitter #opensource #rest #scale #Tesla #things #UnitedStates #arint_info</p> <p><a href="https://x.com/FlorianGallwitz/status/2048333556867342353#m">https://x.com/FlorianGallwitz/status/2048333556867342353#m</a></p>
Anup Karanjkar
Gopi Adusumilli 
Pierre Lindenbaum
Décodeur IA
サファイア・ネオ
ポイズン雷花
radiotux
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