Actualités informatique
Ir al canal en Telegram
1 268
Suscriptores
Sin datos24 horas
-77 días
-3330 días
Carga de datos en curso...
Canales Similares
Nube de Etiquetas
Menciones Entrantes y Salientes
---
---
---
---
---
---
Atraer Suscriptores
octubre '26oct '26
octubre '260
en 0 canales
septiembre '26
+4
en 0 canales
Get PRO
agosto '26
+5
en 0 canales
Get PRO
julio '26
+6
en 0 canales
Get PRO
junio '26
+49
en 0 canales
Get PRO
mayo '26
+159
en 0 canales
Get PRO
abril '26
+57
en 0 canales
Get PRO
marzo '26
+11
en 0 canales
Get PRO
febrero '26
+19
en 0 canales
Get PRO
enero '26
+6
en 0 canales
Get PRO
diciembre '25
+4
en 0 canales
Get PRO
noviembre '25
+4
en 0 canales
Get PRO
octubre '250
en 0 canales
Get PRO
septiembre '25
+2
en 5 canales
Get PRO
agosto '25
+4
en 0 canales
Get PRO
julio '25
+13
en 0 canales
Get PRO
junio '25
+10
en 0 canales
Get PRO
mayo '25
+33
en 10 canales
Get PRO
abril '25
+38
en 0 canales
Get PRO
marzo '25
+35
en 26 canales
Get PRO
febrero '25
+40
en 0 canales
Get PRO
enero '25
+62
en 0 canales
Get PRO
diciembre '24
+30
en 28 canales
Get PRO
noviembre '24
+89
en 26 canales
Get PRO
octubre '24
+92
en 51 canales
Get PRO
septiembre '24
+90
en 34 canales
Get PRO
agosto '24
+111
en 39 canales
Get PRO
julio '24
+88
en 46 canales
Get PRO
junio '24
+82
en 47 canales
Get PRO
mayo '24
+106
en 52 canales
Get PRO
abril '24
+91
en 51 canales
Get PRO
marzo '24
+78
en 68 canales
Get PRO
febrero '24
+109
en 31 canales
Get PRO
enero '24
+155
en 26 canales
Get PRO
diciembre '23
+110
en 0 canales
Get PRO
noviembre '23
+22
en 0 canales
Get PRO
octubre '23
+28
en 0 canales
Get PRO
septiembre '23
+19
en 0 canales
Get PRO
agosto '23
+38
en 0 canales
Get PRO
julio '23
+20
en 0 canales
Get PRO
junio '23
+23
en 0 canales
Get PRO
mayo '23
+24
en 0 canales
Get PRO
abril '23
+18
en 0 canales
Get PRO
marzo '23
+24
en 0 canales
Get PRO
febrero '23
+15
en 0 canales
Get PRO
enero '23
+33
en 0 canales
Get PRO
diciembre '22
+30
en 0 canales
Get PRO
noviembre '22
+41
en 0 canales
Get PRO
octubre '22
+30
en 0 canales
Get PRO
septiembre '22
+26
en 0 canales
Get PRO
agosto '22
+27
en 0 canales
Get PRO
julio '22
+50
en 0 canales
Get PRO
junio '22
+77
en 0 canales
Get PRO
mayo '22
+109
en 0 canales
Get PRO
abril '22
+232
en 0 canales
Get PRO
marzo '22
+622
en 0 canales
Get PRO
febrero '22
+459
en 0 canales
Get PRO
enero '22
+202
en 0 canales
Get PRO
diciembre '21
+203
en 0 canales
Get PRO
noviembre '21
+329
en 0 canales
| Fecha | Crecimiento de Suscriptores | Menciones | Canales | |
| 07 octubre | 0 | |||
| 06 octubre | 0 | |||
| 05 octubre | 0 | |||
| 04 octubre | 0 | |||
| 03 octubre | 0 | |||
| 02 octubre | 0 | |||
| 01 octubre | 0 |
Publicaciones del Canal
Téléchargez pratiquement tous les animes que vous voulez, il suffit de bien écrire le titre de l'anime en question.
@A_Animes_bot
N'oubliez pas d'écrire au support si vous remarquez un souci, un bug ou qqch qui ne fonctionne pas.
| 2 |  ❌Que de 🍆🍑 ❌
👇👇👇👇👇👇👇👇
t.me/Auto_ROLL/999997830999990 | 1 |
| 3 | Un peu de sexe , un peu de coupon
🔞👇👇🔞👇👇🔞👇
t.me/Auto_ROLL/999997830999990 | 1 |
| 4 | Un peu de sexe , un peu de coupon
🔞👇👇🔞👇👇🔞👇
t.me/Auto_ROLL/999997830999990 | 1 |
| 5 | mics an application’s structure and performance characteristics, enabling a wide range of studies.
She expects her work to continue shifting as machine-learning models become more advanced, opening new possibilities to boost application performance and hardware efficiency.
“But you still have to use AI carefully. While it can greatly accelerate the application development side, we still need to audit it and be especially careful about how these models are applied so we don’t lose the ability to gain insights out of the solutions AI is giving,” she says.
Outside the lab, Delimitrou enjoys spending time with her husband and 1-year-old daughter.
While she doesn’t have as much time for hobbies these days, she also enjoys gardening and building an electrical toy train track for her daughter, as well as playing classical piano and painting nature scenes. She became interested in painting at Cornell, where she would often paint the many waterfalls near the campus.
Whether she is working in the garden or painting, Delimitrou says she finds spending time outdoors to be a relaxing escape from the technical nature of her work, but also an important reminder of the role her research plays in sustainability. | 1 |
| 6 | ing these systems.”
Applying AI
To push that utilization closer to 100 percent, she began investigating machine-learning solutions to streamline cumbersome computational processes. Machine learning could automate resource management operations in the cloud, identifying solutions that developers might miss on their own.
“Applying machine learning to solve a large-scale system problem was a novel approach at the time. It was a bit risky because people had not yet shown that these techniques would work,” Delimitrou says. “But empirical approaches require a lot of expertise, and the scale of the system is so large that it is difficult for users to manage. This is why machine learning is often the best solution.”
After earning her PhD, Delimitrou continued this line of work as an assistant professor at Cornell University.
One tool her group developed, Seer, uses deep learning to anticipate and prevent problems in web applications before they happen. This averts widespread slowdowns that may occur if a developer tries to fix a problem manually.
As she delved deeper into cloud computing, Delimitrou observed that cloud applications were changing. Developers were now splitting applications into smaller pieces to spread across multiple servers, which increases the speed of deployment.
“But the servers were not built for this new style of application design. So, I rethought some of my earlier work to build machine-learning systems for this new class of applications,” she says.
To tackle these new challenges, she found herself collaborating more often with faculty members who had different software and hardware expertise. Those collaborations opened exciting new research areas.
A few years later, she decided to join MIT because of the opportunity to collaborate with researchers at the top of their fields in hardware and software engineering. She became an assistant professor in EECS in 2022.
Creative approaches
At MIT, Delimitrou also enjoys the teaching aspect of her role. One of her favorite courses to teach is 6.191 (Computation Structure), a popular undergraduate class with about 350 students each semester.
While it’s challenging to keep the course material fresh when the field constantly evolves, she strives to inspire creativity in her students.
“I want the students to learn how to think and learn on their own. Part of that involves shifting away from formulaic assignments and making classes more open-ended. I’d rather give the students something to make them think more deeply,” she says.
In the lab, a creative mindset helps Delimitrou and her team identify novel solutions to problems in cloud computing that others might overlook.
For instance, she extended prior work on debugging problems in cloud applications to encompass not just errors in the code, but also security issues that can make user data vulnerable to hackers.
She also uses AI to redesign software systems so they better fit the capabilities of existing hardware.
“One of the challenges when it comes to applying AI to these systems is that the AI is not interpretable,” she says. “A lot of the work we are doing now involves adding explainability into these AI tools so people can get useful feedback from the system.”
That not only helps developers ensure AI is giving the right answer, but also provides insights into how to design systems better in the future.
She finds that studying these large-scale cloud computing systems is becoming more challenging because tech companies that operate data centers use proprietary hardware, unlike the commodity equipment of early cloud computing days, as well as software systems that can’t be accessed by academic teams. A solution that works in the lab might not work in the real world.
To that end, Delimitrou and her group create clones of proprietary systems and applications. One tool they developed, called Ditto, mi[...] | 1 |
| 7 | MIT News - Computer Science and Artificial Intelligence Laboratory (CSAIL) Using AI to mitigate the growing environmental threat of data centers
The global building boom of power-hungry data centers is straining electrical grids, causing greater reliance on energy from polluting fossil fuels.
Christina Delimitrou, a newly tenured associate professor at MIT, is fighting this environmental threat by rethinking how the computer servers and networking equipment inside those data centers operate.
She and her group apply machine learning to make large-scale data centers more efficient, secure, and reliable. They redesign outdated cloud computing systems, develop methods to manage shared hardware resources, and create streamlined server architectures.
These advances allow data center operators to coax more computational power out of existing hardware.
“If data centers are not utilized to the best of their capabilities, then they will burn much more power than they need to meet growing user demand,” says Delimitrou, the KDD Career Development Associate Professor in Communications and Technology in the Department of Electrical Engineering and Computer Science (EECS) and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL). “There is a lot of bloating, especially on the software side of these systems. If we can remove that bloating in a way that doesn’t compromise performance, then we won’t need to build as many new data centers.”
She also harnesses AI to help programmers find and fix problems in cloud-based applications, like music-streaming services or video conferencing systems. This eliminates application downtime that hampers performance and drains computational resources.
“By managing resources more effectively in the cloud, the end user gets more predictable performance from the application running on their smartphone,” she adds.
Mathematical beginnings
Delimitrou grew up in a midsized town within the vast plains of northern Greece. Her early interest in math and science was sparked, in part, by the ancient history of her homeland, where Euclid and Pythagoras studied mathematical problems more than 2,000 years ago.
“In Greece, there is a long tradition of geometry,” she says.
She also drew scientific inspiration from her parents. Her mother worked as a chemical engineer and her father as a pharmacist — and both encouraged their daughter’s innate curiosity.
Her early affinity for math led Delimitrou to study computer engineering at the National Technical University of Athens, even though she didn’t know much about the field. She quickly gravitated toward courses that focused on the applied science of engineering.
For her diploma thesis — a project all students complete during their fifth and final year of study — she studied resource management in a computer when multiple applications are running at once.
“A lot of the challenges I was looking at then would get much harder if, instead of a single system, you had 100,000 of these systems. That was a problem that piqued my interest,” she says.
Seeking to make a bigger impact as a researcher, Delimitrou pursued a graduate degree at Stanford University. She began tackling inefficiencies in cloud computing systems and large-scale data centers, which was a rapidly growing area of research.
Through that work, Delimitrou and her research mentor, Christos Kozyrakis, the Leonard Bosack and Sandy K. Lerner Professor of Engineering, realized many large computing systems were underutilized.
“You would expect, with all the demand for these systems, that they should be running close to 100 percent capacity. But we found that most were running at only about 15 percent capacity,” she says. “This is not a resource-efficient or sustainable way of scal[...] | 1 |
| 8 | Sin texto... | 1 |
| 9 | 🔞🔞🔞🔞🔞🔞🔞🔞🔞🔞
👇👇👇👇👇👇👇👇👇👇 | 1 |
| 10 | ❌Que de 🍆🍑 ❌
👇👇👇👇👇👇👇👇
t.me/Auto_ROLL/999997830999990 | 1 |
| 11 | Un peu de sexe , un peu de coupon
🔞👇👇🔞👇👇🔞👇
t.me/Auto_ROLL/999997830999990 | 1 |
| 12 | ❌Que de 🍆🍑 ❌
👇👇👇👇👇👇👇👇
t.me/Auto_ROLL/999997830999990 | 1 |
| 13 | InformatiqueNews.fr
IA en entreprise : après l’adoption, le défi de la gouvernance
L’IA fait exploser la production de code. Mais derrière la promesse de vitesse, une autre équation se dessine : qui paie, qui contrôle et comment prouver que ces gains créent vraiment de la valeur ? En quelques années, l’IA s’est imposée comme un nouvel accélérateur de productivité dans les entreprises, notamment dans le développement logiciel. Elle permet […]
L’article IA en entreprise : après l’adoption, le défi de la gouvernance est apparu en premier sur InformatiqueNews.fr. | 2 |
| 14 | Sin texto... | 2 |
| 15 | InformatiqueNews.fr
Strands Box : AWS met les agents IA en cage avant de leur donner les clés
Alors que les sandbox d’OpenAI et Anthropic semblent plus ressembler à des passoires qu’à des bacs à sable protecteurs, AWS lance Strands Box, une sandbox open source qui ajoute aux barrières du système d’exploitation des politiques capables de comprendre ce que fait l’agent… et ce qu’il a fait auparavant. Histoire de pousser le contrôle des […]
L’article Strands Box : AWS met les agents IA en cage avant de leur donner les clés est apparu en premier sur InformatiqueNews.fr. | 2 |
| 16 | Sin texto... | 1 |
| 17 | InformatiqueNews.fr
JADEPUFFER : le ransomware passe en mode agentique
Le ransomware ne se contente plus d’être écrit avec l’aide d’une IA. Désormais, l’IA peut aussi lui-même être le ransomware en conduisant une bonne partie de l’attaque, en s’adaptant aux obstacles et en enchaînant les étapes jusqu’à la destruction des données. Avec JADEPUFFER, documenté par Sysdig puis retrouvé par Microsoft, la cybercriminalité vient de franchir […]
L’article JADEPUFFER : le ransomware passe en mode agentique est apparu en premier sur InformatiqueNews.fr. | 1 |
| 18 | Sin texto... | 1 |
| 19 | InformatiqueNews.fr
Microsoft change d’échelle : Windows devient la plateforme d’exécution des agents IA
Microsoft et Nvidia dévoilent une nouvelle génération de PC capables d’exécuter localement des modèles dépassant 120 milliards de paramètres. Mais le Surface Laptop Ultra et ses 128 Go de mémoire unifiée ne racontent qu’une partie de l’histoire. Derrière le matériel, Microsoft assemble les briques d’un Windows capable de répartir l’IA entre NPU, GPU et cloud, d’exécuter localement des modèles avancés, mais aussi d’isoler, d’identifier et d’administrer les agents qui vont progressivement s’installer sur nos postes de travail.
L’article Microsoft change d’échelle : Windows devient la plateforme d’exécution des agents IA est apparu en premier sur InformatiqueNews.fr. | 1 |
| 20 | Sin texto... | 1 |
