manzana Anunció watchOS 11 durante que Conferencia mundial de desarrolladores 2024 Presentación Keynote (Puedes seguir todos los anuncios a medida que ocurren en nuestro sitio web Blog en vivo de la WWDC 2024), y hay mucho en lo que sumergirse, incluidas funciones mejoradas de watchOS 10, como un conjunto de herramientas más inteligente con Live Activity y funciones completamente nuevas como Training Load y la nueva aplicación Vitals.
watchOS 11 debuta con una serie de funciones nuevas, incluida una nueva puntuación de carga de entrenamiento. Utilizando métricas como el reposo y la frecuencia cardíaca promedio, junto con estadísticas como la edad y el peso, el algoritmo de Apple genera una puntuación de carga de entrenamiento que cambia constantemente, lo que puede ayudar a los atletas que usan… Los mejores relojes Apple Para realizar un seguimiento de la actividad, calcule cuánto entrenaron durante un período de tiempo determinado.
Si estás entrenando demasiado duro, Apple podrá decírtelo y al mismo tiempo marcará nuevas métricas como la distancia de carrera semanal para garantizar que te mantengas encaminado hacia tus objetivos (o que sepas cuándo necesitas tomar un descanso).
(Crédito de la imagen: Apple)
Apple también está presentando una nueva aplicación Vitals, que está diseñada para ayudar a comprender cómo responde su cuerpo al estrés y se recupera del mismo. Desarrollado utilizando datos del Estudio del Corazón y el Movimiento de Apple, Apple observará su frecuencia cardíaca, frecuencia respiratoria, sueño y otras métricas y las comparará con su rango promedio. Si varias métricas se marcan como inusuales, reloj de manzana Yo lo haré saber. La aplicación Salud le pedirá que revise aspectos de su vida, como su horario de sueño, niveles de ejercicio y consumo de alcohol.
Por otra parte, el paquete de widgets recibe una revisión con actividades en vivo. Los widgets ya no son estáticos: puedes ver cuándo está programado que llegue tu auto Uber en el widget de la pantalla de inicio sin abrir la aplicación, o usar la función de inicio de sesión de Apple (anteriormente solo disponible en iPhone) para informar a tus amigos cuando has llegado. llegó a casa. Apple también lanzó una etiqueta en la aplicación Baby Monitor y estamos seguros de que más desarrolladores introducirán nuevas funciones interesantes con las que interactuar directamente desde el kit de herramientas.
Apple no ha declarado directamente qué relojes Apple serán compatibles con watchOS 11, pero los primeros informes afirman que Apple dejará de admitir el Apple Watch Series 4, Series 5 y el Apple Watch SE original.
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Cybersecurity and compliance training programs are now big business. According to Cybersecurity Ventures, the security awareness training market hit $5.6 billion in 2023 and is expected to surpass $10 billion in the next four years. This market boom is no surprise: cyber threats are rampant and large-scale attacks continue making headlines, most recently hitting the British Library, just to name a UK example, and disrupting their ability to function. All of this proves that every organization, no matter its size, is at risk of a breach.
Social engineering techniques, where an attacker targets the people who have access to systems (rather than the systems themselves) and manipulates them into handing over control, were the most popular malicious tactics in 2023. Businesses are therefore correct to recognize that people are a key vulnerability.
Annual cybersecurity awareness training is a regular feature on the calendar for most organizations in an attempt to ensure that every person within every department develops their cyber awareness skills, and is able to spot threats and respond accordingly before they become a major issue. In the face of fast-evolving security threats, this training is often outdated and can take months or even years later to bring that education to help people recognize the tactics used.
Neil Thacker
Chief Information Security Officer EMEA, Netskope.
Should training come around quicker than every year?
Ask any security leader and they wouldn’t be hard pressed to admit that employees find annual cybersecurity training time-consuming and uninspiring. Often viewed as a distraction for an employee, many will click through, skim read, watch videos at double-speed and pursue whatever shortcuts they can find to reach the completion certificate, check the box and carry on with their working day.
What’s more, the often limited interactivity of each annual training course fails to capture and maintain employees’ attention. Retention rates plummet without active engagement, and many training schemes lack any form of connecting the employee to real-world scenarios that could occur in their specific job function.
Even for those outliers who find annual training engaging and insightful, there is still little evidence it truly educates individuals or leads to positive behavior changes. As a result, they serve as little more than compliance checkboxes, as opposed to being a proactive measure to build a culture of vigilance and defend against threats. Ultimately, it’s not an efficient use of both time and resources, and cyber attacks continue their steady momentum.
It’s worth also noting that malicious actors specifically build their campaigns in a way that even the best trained employee forgets their general cybersecurity logic. This includes preying on emotional – rather than logical – behavior, and harnessing a sense of urgency to specifically guide the victim out of their logical and trained approach.
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So, how do we go beyond education? Organizations everywhere need behavioral intervention that helps to point people back toward logical thinking before they take big cyber risks.
Nudging toward greater cyber hygiene
Small, regular and human-centric intervention is an ideal route for effective long-term behavioral shifts. An example of this is nudge theory – a general set of principles aimed to guide human behavior down a more desirable path. It’s a well-established concept that has been hugely successful in the past, steering people toward healthier food choices and pro-environmental behavior, and requires only small changes in decision making at crucial moments when they’re moving through (often automatic) behaviors. Applying this to the world of cybersecurity, therefore, feels like a no brainer.
In the same way that radar speed signs show your current speed – giving you a second to think and adapt your behavior – we should have signals at work letting us know when we’re about to participate in risky cyber behavior and encourage us to slow down and think.
This human-centric route of prevention can be highly effective, and is a tool that should be more widely known and accessible for enterprises. Real time user coaching, for example, harnesses AI detection to instantly flag a high risk behavior to the individual as it happens, and propose alternative actions for the employee.
This is particularly important in the age of Generative AI, where third party AI tools are freely available across many enterprises, and platforms such as ChatGPT and Google Bard are seen as the go-to assistant for many admin tasks. The risk here is that many employees are uploading sensitive data to these platforms (from source code to personally identifiable information) and significantly increasing the risk of a data loss.
In most cases, employees accessing these services are unaware of the risk and are trying to be productive with tools they are familiar with or have stumbled across. Rather than blocking this activity outright, potentially leading to a disgruntled employee who works harder to get around the policy, just-in-time employee coaching provides an opportunity to explain the risk in the moment as it arises – crafted to fit company culture and tone of voice, as well as policy – and recommend safer ways to achieve the same outcome.
Continuous education
This form of continuous education and reinforcement can provide for employees what annual training lacks: an opportunity to contextualize information and prevent it from fading quickly in memory. What’s more, this practical application of consistent reminders in an employee’s everyday working life is the essential ingredient to fully understand and harness greater cyber hygiene.
By coaching employees in real-time to become better cyber citizens and make safer decisions, businesses can prevent cyber incidents the moment the threat occurs, and build genuine learning opportunities into employees’ daily working lives.
Rather than viewing humans as a weak link in our security posture, we should approach them as our last line of defense between an enterprise and the cyber threat landscape. It’s important that we recognize that, and train people in the way that is going to be most effective and empowering.
This article was produced as part of TechRadarPro’s Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro
If you own one of the best Garmin watches and you want to start training for a race, then you have a pretty useful tool in your armory in the shape of Garmin Coach.
Garmin Coach is Garmin’s own training platform built for runners and cyclists. of all abilities that know they need a training plan and don’t know where to start. Best of all, once created, that plan will then live on your watch, serving up the runs you need to when it’s time to train.
Those plans will also change based on your performance in your training or if you need to skip a workout for any reason.
If you like the idea of what Garmin Coach promises to do, but you’re unsure how to find it or how to get started with it, here’s a simple breakdown of how to use Garmin Coach platform.
Once you’re in that Training Plan section tap to proceed to the next screen to find your plan. Currently, Garmin Coach is only available for running and cycling. For simplicity, we’ll focus on showing you how to create a running plan using your best running watch, though there will be similarities when choosing to do a cycling one.
Under Running, you’ll find three different coaching plans. Those are for 5k, 10k and a half marathon. There isn’t currently an option for training for a marathon.
For each plan, you’ll find a description for the type of level of runner they’re best suited for. So for the 5k plan, you’ll see that it’s designed for beginner runners and intermediate runners. For the half marathon plan, you’ll see that it’s designed for intermediate runners.
After you’ve read through the terms and conditions and are happy to proceed, you will be asked how much running you currently do, from “I don’t run” to “40 kilometers or more”. This will help shape the plan based on your running experience.
Next, you’ll be asked your average running pace. If you don’t know this, a simple way to work it out is to divide a distance you’ve run by the time it took you to run that distance. A quick Google of ‘pace calculator’ will also help you work this out as well.
While you won’t have a coach physically telling you what to do, you will have a plan devised by a running coach that will shape the training schedule and even the length that training will take to get you to your goal. Garmin offers three coach options, all with accompanying videos to tell you about their approach to training to help you make the best choice for you.
Once you’ve decided, select a coach and then you’ll be asked how many workouts you’d like to commit to per week. You can also pick the days where you’re available to fit training into your routine. You’ll also need to pick a day where you can do your ‘long run’.
A long run is typically deemed to be anything longer than 5 miles (8km), though this will entirely depend on the type of distance you’re training for.
Once you’ve done that last step you’ll get a summary of the key details your plan will be built around. Hit create plan, and you’ll be prompted when your first planned run will take place.
How to follow your Garmin Coach plan on your watch
One of the great things about Garmin Coach is that once created in the Garmin Connect app you can share it with your watch. That way you can check on your upcoming training without delving into the app. When you start to track a run on the days you also have a training run planned for, it will display the suggested run for that day based on your plan.
To do this, you need to share the plan to your watch and it’s simply done. Go to the Home page on Garmin Connect app, look to the top of the page for the icon of your watch and press the two arrows in a circle to sync your plan to the watch.
If you have access to your calendar enabled on your watch, you’ll also be able to see when your next planned run is scheduled for by scrolling down from the main watch screen to your Glances (widgets) screen.
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If you skip a workout, the plan will automatically adjust to factor that in. If you skip too many workouts, the plan will display a message asking if you want to pause the plan.
How to reschedule a training run on Garmin Coach
You can also reschedule workouts in the Garmin Connect app, as long as you’ve done it enough in advance for it to be adjusted. To do this, go to your training plan in the Garmin Connect app. Select your training plan and press the three dotted icon and select Reschedule. Once confirmed, you’ll need to sync the changes to your watch again to update your plan.
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Cybersecurity training for the ultimate IT job
Not everyone dreams of working at an Apple Store. As anyone with a career in tech knows, it’s hard to make progress on an IT job without earning the necessary certifications.
This cybersecurity training bundle includes a whopping eight prep courses. The classes cover all sorts of IT certifications, from pen testing to Cisco — all taught by experts like David Bombal and Total Seminars.
Here’s what this training bundle covers:
Cisco CCNA 200-301 Exam: Complete Course with Practical Labs: This course will prep you for the newest CCNA 200-301 exam — the first step toward attaining your Cisco certifications. This course also will help you keep up with the growth of the internet of things. (The course earned a 4.6 out of 5 star rating.)
CompTIA IT Fundamentals ITF+ FC0-U61: A prerequisite before moving on to more complicated exams, this course teaches you security, safety and preventative maintenance, as well as the basics of databases and programming.
CompTIA A+ Certification Core 1 (220-1001): The CompTIA A+ certification is the industry standard for establishing a career in IT. This course covers mobile devices, networking technology, hardware, network troubleshooting and virtualization, and cloud computing.
CompTIA A+ Certification Core 2 (220-1002): This credential helps you gain the trust of global employers for endpoint management and technical support roles.
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CompTIA Security+ Certification SY0-501: Gain access to 121 lectures led by the industry’s leading authority on CompTIA certifications. The coursework focuses on the latest trends and techniques in risk management, risk mitigation, threat management and intrusion detection.
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Even the most advanced fitness trackers can’t catch everything. While testing the Garmin Forerunner 165 Music, I got a severe case of food poisoning and spent two days in bed. There’s nothing more irritating than your cheery fitness tracker notifying you that you’ve gotten tons of sleep and your Body Battery is at 100 as you’re struggling not to throw up water. It’s almost as irritating as your children shouting to ask if you’re still trapped in the bathroom.
When I finally got back to working out, the watch counseled me to build up my base with long, slow runs. This pace is insanely slow, particularly since I live next to a college campus full of long-legged teenagers, humiliating me with their vigorous strides, youthfulness, and hope. Nevertheless, I persist. My legs feel great. The Forerunner has allowed me to graduate to tempo runs, and my heart rate is lower than ever. Amazing!
The Forerunner 165 is the latest entry in Garmin’s Forerunner series, but there are no duds in the Forerunner lineup. If you’re a beginner runner who can find the barebones Forerunner 55 for under $200, that one is perfectly fine! However, the Forerunner 165 has enough additional features that, to me, it justifies the extra cash.
A Few More Features
The Forerunner 165 looks like your standard technical Garmin. It has the familiar five-button layout—three on the left and two on the right—with a chemically reinforced screen, a polymer bezel, and a silicone strap. Note: You will need to wash the strap every two to three days if you don’t want to get a wrist rash. It now also has a new, bright AMOLED display that I had no problem seeing in bright, direct sunlight.
Photograph: Adrienne So
It’s also a touchscreen, so instances where I spectacularly fail at navigating the button system have decreased dramatically. Same with times where I accidentally call my emergency contacts from holding the wrong button down for too long. (It’s the Up button on the left side. Don’t hold that button unless you’re in trouble.)
The higher-end Forerunner models are aimed at multisport athletes, but the Forerunner 165 is pretty explicitly aimed at runners. In addition to personalized, adaptive training plans, you can also now see metrics like running power and cadence on the screen on your wrist, as well as some of Garmin’s more esoteric proprietary metrics, like Training Effect, which helps you determine how impactful each workout was on your overall performance.
The reason you get a Forerunner 165 over a Forerunner 55 is that in addition to a nicer display, you also get more sensors. In addition to the now-standard multiband GPS positioning systems—GPS, Glonass, and Galileo, which lets you position yourself precisely for accurate workout metrics—the Forerunner 165 has the pulse oximetry blood oxygen sensor, as well as a barometric altimeter, compass, and ambient light sensor.
Samsung is reportedly planning to launch its own AI accelerator chip, the ‘Mach-1’, in a bid to challenge Nvidia‘s dominance in the AI semiconductor market.
The new chip, which will likely target edge applications with low power consumption requirements, will go into production by the end of this year and make its debut in early 2025, according to the Seoul Economic Daily.
The announcement was made during the company’s 55th regular shareholders’ meeting. Kye Hyun Kyung, CEO of Samsung Semiconductor, said the chip design had passed technological validation on FPGAs and that finalization of SoC was in progress.
Entirely new type of AGI semiconductor
The Mach-1 accelerator is designed to tackle AI inference tasks and will reportedly overcome the bottleneck issues that arise in existing AI accelerators when transferring data between the GPU and memory. This often results in slower data transmission speeds and reduced power efficiency.
The Mach-1 is reportedly a ‘lightweight’ AI chip, utilizing low-power (LP) memory instead of the costly HBM typically used in AI semiconductors.
The move is widely seen as Samsung’s attempt to regain its position as the world’s largest semiconductor company, fighting back against Nvidia which completely dominates the AI chip market and has seen its stock soar in recent months, making it the third most valuable company in the world behind Microsoft and Apple.
While the South Korean tech behemoth currently has no plans to challenge Nvidia’s H100, B100, and B200 AI powerhouses, Seoul Economic Daily reports that Samsung has established an AGI computing lab in Silicon Valley to expedite the development of AI semiconductors. Kyung stated that the specialized lab is “working to create an entirely new type of semiconductor designed to meet the processing requirements of future AGI systems.’
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The surge in demand for large-scale generative AI models has led to a significant increase in hardware requirements, making model training costly and inaccessible for many SMBs and educational establishments.
High-performance custom PC builder Maingear has partnered with storage giant Phison on a new range of Maingear Pro AI workstations that boast powerful Intel Xeon W7-3455 CPUs.
The new workstations can be configured with up to 1TB of DDR5 memory, and up to 4x RTX 5000 Ada or 4x RTX 6000 Ada GPUs. These GPUs are supported by Phison aiDAPTIV+ caching SSDs and software, to significantly lower the cost of LLM development and training.
Off-the-shelf components
Maingear Pro AI workstations fit in a standard desktop tower PC design so they can easily be stored under a desk, or placed anywhere in an office (a 4U rackmount chassis is also available). Maingear says these workstations have been designed with off-the-shelf components for easy upgrades and Noctua cooling components to manage heat and reduce noise when under load.
Maingear founder and CEO, Wallace Santos, stated, “Our dedication to crafting highly capable yet budget-friendly solutions guarantees SMBs, universities, and research facilities a competitive advantage in an industry formerly restricted by multimillion-dollar investments.”
Meta has unveiled details about its AI training infrastructure, revealing that it currently relies on almost 50,000 Nvidia H100 GPUs to train its open source Llama 3 LLM.
The company says it will have over 350,000 Nvidia H100 GPUs in service by the end of 2024, and the computing power equivalent to nearly 600,000 H100s when combined with hardware from other sources.
The figures were revealed as Meta shared details on its 24,576-GPU data center scale clusters.
The company explained “These clusters support our current and next generation AI models, including Llama 3, the successor to Llama 2, our publicly released LLM, as well as AI research and development across GenAI and other areas.“
The clusters are built on Grand Teton (named after the National Park in Wyoming), an in-house-designed, open GPU hardware platform. Grand Teton integrates power, control, compute, and fabric interfaces into a single chassis for better overall performance and scalability.
The clusters also feature high-performance network fabrics, enabling them to support larger and more complex models than before. Meta says one cluster uses a remote direct memory access network fabric solution based on the Arista 7800, while the other features an NVIDIA Quantum2 InfiniBand fabric. Both solutions interconnect 400 Gbps endpoints.
“The efficiency of the high-performance network fabrics within these clusters, some of the key storage decisions, combined with the 24,576 NVIDIA Tensor Core H100 GPUs in each, allow both cluster versions to support models larger and more complex than that could be supported in the RSC and pave the way for advancements in GenAI product development and AI research,” Meta said.
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Storage is another critical aspect of AI training, and Meta has developed a Linux Filesystem in Userspace backed by a version of its ‘Tectonic’ distributed storage solution optimized for Flash media. This solution reportedly enables thousands of GPUs to save and load checkpoints in a synchronized fashion, in addition to “providing a flexible and high-throughput exabyte scale storage required for data loading”.
While the company’s current AI infrastructure relies heavily on Nvidia GPUs, it’s unclear how long this will continue. As Meta continues to evolve its AI capabilities, it will inevitably focus on developing and producing more of its own hardware. Meta has already announced plans to use its own AI chips, called Artemis, in servers this year, and the company previously revealed it was getting ready to manufacture custom RISC-V silicon.
Samsung has announced a new partnership with FlexIt for online health and wellness training on Samsung Daily+, this new partnership is designed to make exercise more accessible and also more convenient.
The new partnership will bring personal trainer-based fitness training to Samsung Smart TVs through Samsung’s new lifestyle hub which is called Samsing Daily+, there will be a wide range of fitness content available.
“Wellness should be central to our routines, so building healthy habits through Samsung Daily+ makes it convenient to incorporate health and wellness into all different aspects of daily life,” said Demian Hyun, Vice President and Head of the Experience Planning Group of Visual Display Business at Samsung Electronics. “This new partnership underscores Samsung’s commitment as the leader in the global display industry to promoting thoughtful, interconnected health experiences aimed at bettering the lives of consumers.”
On the FlexIt app’s online portal, users can find, book and pay for exclusive one-on-one virtual fitness sessions directly on their TVs. With a camera connected — whether it be via a supported webcam3 or a smartphone — virtual health professionals4 provide real-time feedback, adjust workouts, and offer form modifications to foster a supportive, safe, and effective workout environment.
You can find out more information about the new fitness content coming to Samsung’s Smart TVs and also Samsung Daily+ over at Samsung’s website at the link below.
Source Samsung
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Artificial intelligence seems to be on the brink of another significant transformation nearly every week at the moment, and this week is no exception. As developers, businesses and researchers dive deeper into the capabilities of large language models (LLMs) like GPT-4, we’re beginning to see a shift in how these systems tackle complex problems. The human brain operates using two distinct modes of thought, as outlined by Daniel Kahneman in his seminal work, “Thinking, Fast and Slow.” The first, System 1, is quick and intuitive, while System 2 is slower, more deliberate, and logical. Until now, AI has largely mirrored our instinctive System 1 thinking, but that’s changing.
In practical terms, System 2 thinking is what you use when you need to think deeply or critically about something. It’s the kind of thinking that requires you to stop and focus, rather than react on instinct or intuition. For example, when you’re learning a new skill, like playing a musical instrument or speaking a foreign language, you’re primarily using System 2 thinking.
Over time, as you become more proficient, some aspects of these skills may become more automatic and shift to System 1 processing. Understanding the distinction between these two systems is crucial in various fields, including decision-making, behavioral economics, and education, as it helps explain why people make certain choices and how they can be influenced or trained to make better ones.
AI System 2 thinking
Researchers are now striving to imbue AI with System 2 thinking to enable deeper reasoning and more reliable outcomes. The current generation of LLMs can sometimes produce answers that seem correct on the surface but lack a solid foundation of analysis. To address this, new methods are being developed. One such technique is prompt engineering, which nudges LLMs to unpack their thought process step by step. This is evident in the “Chain of Thought” prompting approach. Even more advanced strategies, like “Self-Consistency with Chain of Thought” (SCCT) and “Tree of Thought” (ToT), are being explored to sharpen the logical prowess of these AI models.
The concept of collaboration is also being examined as a way to enhance the problem-solving abilities of LLMs. By constructing systems where multiple AI agents work in concert, we can create a collective System 2 thinking model. These agents, when working together, have the potential to outperform a solitary AI in solving complex issues. This, however, introduces new challenges, such as ensuring the AI agents can communicate and collaborate effectively without human intervention.
Other articles you may find of interest on the subject of training large language models :
To facilitate the development of these collaborative AI systems, tools like Autogen Studio are emerging. They offer a user-friendly environment for researchers and developers to experiment with AI teamwork. For example, a problem that might have been too challenging for GPT-4 alone could potentially be resolved with the assistance of these communicative agents, leading to solutions that are not only precise but also logically sound.
What will AI be able to accomplish with System 2 thinking?
As we look to the future, we anticipate the arrival of next-generation LLMs, such as the much-anticipated GPT-5. These models are expected to possess even more advanced reasoning skills and a deeper integration of System 2 thinking. Such progress is likely to significantly improve AI’s performance in scenarios that require complex problem-solving.
The concept of System 2 thinking, as applied to AI and large language models (LLMs), involves the development of AI systems that can engage in more deliberate, logical, and reasoned processing, akin to human System 2 thinking. This advancement would represent a significant leap in AI capabilities, moving beyond quick, pattern-based responses to more thoughtful, analytical problem-solving. Here’s what such an advancement could entail:
Enhanced Reasoning and Problem Solving: AI with System 2 capabilities would be better at logical reasoning, understanding complex concepts, and solving problems that require careful thought and consideration. This could include anything from advanced mathematical problem-solving to more nuanced ethical reasoning.
Improved Understanding of Context and Nuance: Current LLMs can struggle with understanding context and nuance, especially in complex or ambiguous situations. System 2 thinking would enable AI to better grasp the subtleties of human language and the complexities of real-world scenarios.
Reduced Bias and Error: While System 1 thinking is fast, it’s also more prone to biases and errors. By incorporating System 2 thinking, AI systems could potentially reduce these biases, leading to more fair and accurate outcomes.
Better Decision Making: In fields like business or medicine, where decisions often have significant consequences, AI with System 2 thinking could analyze vast amounts of data, weigh different options, and suggest decisions based on logical reasoning and evidence.
Enhanced Learning and Adaptation: System 2 thinking in AI could lead to improved learning capabilities, allowing AI to not just learn from data, but to understand and apply abstract concepts, principles, and strategies in various situations.
More Effective Human-AI Collaboration: With System 2 thinking, AI could better understand and anticipate human needs and behaviors, leading to more effective and intuitive human-AI interactions and collaborations.
It’s important to note that achieving true System 2 thinking in AI is a significant challenge. It requires advancements in AI’s ability to not just process information, but to understand and reason about it in a deeply contextual and nuanced way. This involves not only improvements in algorithmic approaches and computational power but also a better understanding of human cognition and reasoning processes. As of now, AI, including advanced LLMs, primarily operates in a way that’s more akin to human System 1 thinking, relying on pattern recognition and rapid response generation rather than deep, logical reasoning.
The journey toward integrating System 2 thinking into LLMs marks a pivotal moment in the evolution of AI. While there are hurdles to overcome, the research and development efforts in this field are laying the groundwork for more sophisticated and dependable AI solutions. The ongoing dialogue about these methods invites further investigation and debate on the most effective ways to advance System 2 thinking within artificial intelligence.
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