Introduction to the Experiment

During a recent executive program, we conducted a micro-experiment. Participants opted to surrender their mobile phones for one evening and get them back the next morning.

Reflection and Observations

Participants were asked to reflect on their thoughts, emotions, and behaviors during the experiment. The next morning was full of discussion: Some had noticed themselves reaching for their phones mindlessly, coupled with jolts of “panic” when finding it missing; some felt irritable or frustrated about not being able to look things up on demand; some were nervous to wander the city’s streets without their GPS; while others rationalized the reasons they urgently needed their phone or felt extreme fear of missing out.

Outcomes and Insights

At the same time, many felt liberated, noticing more around them and enjoying the freedom of not accessing work emails in the evening. Almost all learned something about themselves.

Conclusion

The experiment provided valuable insights into the participants’ relationship with their mobile phones. It highlighted the emotional attachment people have with their devices and how they can impact daily life. By surrendering their phones, participants were able to identify their mindless habits, experience a range of emotions, and appreciate the freedom that comes with being disconnected. The experiment served as a catalyst for self-reflection, allowing participants to gain a deeper understanding of themselves and their dependence on technology.

FAQs

What was the purpose of the experiment?

The purpose of the experiment was to help participants reflect on their thoughts, emotions, and behaviors in relation to their mobile phone use.

What did participants have to do during the experiment?

Participants had to surrender their mobile phones for one evening and return them the next morning.

What were some common reactions during the experiment?

Common reactions included feeling irritable, frustrated, nervous, or experiencing a fear of missing out. However, many participants also felt liberated and enjoyed the freedom from constant connectivity.

What was the outcome of the experiment?

The experiment helped participants learn something about themselves and their relationship with their mobile phones, promoting self-reflection and a deeper understanding of their dependence on technology.

Introduction to AI Inference Processing

Everyone is not just talking about AI inference processing; they are doing it. Analyst firm Gartner released a new report this week forecasting that global generative AI spending will hit $644 billion in 2025, growing 76.4% year-over-year. Meanwhile, MarketsandMarkets projects that the AI inference market is expected to grow from $106.15 billion in 2025 to $254.98 billion by 2030. However, buyers still need to know what AI processor to buy, especially as inference has gone from a simple one-shot run through a model to agentic and reasoning models that can increase computational requirements by some 100-fold.

Performance Continues to Skyrocket

For seven years, the not-for-profit group MLCommons has been helping AI buyers and vendors by publishing peer-reviewed quarterly AI benchmarks. It has just released its Inference 5.0 suite of results, with new chips, servers, and models. Let’s take a look.

The New Benchmarks

New benchmarks were added for the larger Llama 3.1 405B, Llama 2 70B with latency constraints for interactive work, and a new “R-GAT” benchmark for graph models. Only Nvidia ran benchmarks for all the models. A new benchmark was also added for edge inference, the Automotive PointPainting test for 3D object detection. There are now 11 AI benchmarks managed by MLCommons.

The New Chips

AI is built on silicon, and MLCommons received submissions for six new chips this round, including AMD Instinct MI325X (launched last Fall), Intel Xeon 6980P “Granite Rapids” CPU, Google TPU Trillium (TPU v6e) which has become generally available, Nvidia B200 (Blackwell), Nvidia Jetson AGX Thor 128 for AI at the Edge, and perhaps most importantly the Nvidia GB200, the beast that powers the NVL72 rack that has data centers scrambling to power and cool.

The New Results: Nvidia

As usual, Nvidia won all benchmarks; this time, they won by a lot. First, the B200 tripled the performance of the H200 platform, delivering over 59,000 tokens per second on the latency-bounded Llama 2 70B Interactive model. The new Llama 3.2 405B model is 3.4 times faster on Blackwell. Now for the real test: is the NVL72 as fast as Nvidia promised at launch? Yes, it is thirty times faster than the 8-GPU H200 running the new Llama 405B, but it has 9 times more GPUs.

Nvidia Performance

The new Llama 3.1 405B benchmark supports input and output lengths up to 128,000 tokens (compared to only 4,096 tokens for Llama 2 70B). The benchmark tests three distinct tasks: general question-answering, math, and code generation. But when you add Nvidia’s new open-source Dynamo “AI Factory OS” that optimizes AI at the data center level, AI factory throughput can double again running Llama and thirty times faster running DeeSeek.

And, Surprise, AMD Has Rejoined the MLPerf Party!

Welcome back, AMD! The new AMD MI325 did quite well at the select benchmarks AMD ran, competing admirably with the previous generation Hopper GPU. So, for AI practitioners who know what they are doing and don’t need the value of Nvidia software, AMD MI325 can save them a lot of money. AMD also did quite well at the Llama 3.1 405B Serving benchmark (distinct from the interactive 405B benchmark mentioned previously). AMD proudly said that Meta is now using the (older) MI300X as the exclusive inference server for the 405B model.

Conclusion

Nvidia retains the crown of AI King across all AI applications. Although competition is on the horizon, AMD delivers competitive performance only when measured against the previous Nvidia GPU generation. AMD expects that the MI350, due later this year, will close the gap. However, thanks to the GB300, Nvidia will retain the lead at the GPU performance level by then. But the real issue here is that while everyone else is trying to compete at the GPU level, Nvidia keeps raising the bar at the data center level with massive investments in software, solutions, and products to ease AI deployment and lower TCO.

FAQs

• Q: What is the forecast for global generative AI spending in 2025?
  A: Global generative AI spending is expected to hit $644 billion in 2025, growing 76.4% year-over-year.
• Q: What is the projected growth of the AI inference market from 2025 to 2030?
  A: The AI inference market is expected to grow from $106.15 billion in 2025 to $254.98 billion by 2030.
• Q: What is the performance of Nvidia’s B200 chip compared to the H200 platform?
  A: The B200 chip tripled the performance of the H200 platform, delivering over 59,000 tokens per second on the latency-bounded Llama 2 70B Interactive model.
• Q: How does AMD’s MI325 chip perform compared to Nvidia’s Hopper GPU?
  A: The AMD MI325 chip competes admirably with the previous generation Hopper GPU, and can save AI practitioners a lot of money if they don’t need Nvidia’s software.
• Q: What is the significance of Nvidia’s Dynamo "AI Factory OS"?
  A: Nvidia’s Dynamo "AI Factory OS" optimizes AI at the data center level, allowing for doubled throughput and lower TCO.

Introduction to Crafting a Memorable Message

Crafting a memorable message is an art that combines psychology, creativity, and clarity. According to science, the way we structure and deliver our messages significantly influences how they are received and remembered by our audience. Understanding these principles can help individuals, marketers, and communicators of all kinds to convey their ideas more effectively.

Understanding the Psychology of Memory

The Role of Emotions

Emotions play a crucial role in memory formation. Messages that evoke strong emotions, whether positive or negative, are more likely to be remembered. This is because emotional experiences trigger the release of dopamine, a neurotransmitter that enhances memory consolidation. Therefore, incorporating elements that elicit emotions into your message can significantly increase its memorability.

The Power of Storytelling

Storytelling is another powerful tool for crafting memorable messages. Human brains are wired to respond to stories, as they provide context, create emotional connections, and are easier to recall than plain facts and figures. By framing your message within a narrative, you can make it more relatable, engaging, and memorable.

Structuring Your Message

Clarity and Simplicity

Clarity and simplicity are key to a memorable message. A message that is straightforward and easy to understand requires less cognitive effort to process, making it more likely to be remembered. Avoid using jargon or overly complex language that might confuse your audience.

Repetition and Rhythm

Repetition is a fundamental principle of memory. Repeating your key message or using repetitive structures like rhymes can make your message more memorable. Rhythm also plays a role, as messages with a rhythmic quality are easier to remember, a phenomenon often observed in advertising jingles and slogans.

Delivering Your Message

Non-Verbal Communication

Non-verbal cues such as body language, facial expressions, and tone of voice can significantly influence how your message is received. A confident and engaged demeanor can enhance the impact of your message, making it more believable and memorable.

Visual Aids

Visual aids like images, videos, and infographics can also enhance the memorability of your message. Visual information is processed more quickly and is more likely to be remembered than text alone. Incorporating relevant and engaging visual elements can therefore improve the retention of your message.

Conclusion

Crafting a memorable message is a multifaceted task that requires an understanding of human psychology, creativity, and effective communication strategies. By leveraging emotions, storytelling, clarity, repetition, and appropriate delivery methods, including non-verbal cues and visual aids, you can significantly increase the impact and memorability of your message. Whether you’re a marketer, educator, or simply looking to communicate more effectively in your personal life, applying these principles can help ensure your messages are remembered and acted upon.

FAQs

• Q: Why are emotional messages more memorable?
  A: Emotional messages are more memorable because they trigger the release of dopamine, which enhances memory consolidation.
• Q: How does storytelling help in making messages more memorable?
  A: Storytelling makes messages more relatable, engaging, and easier to recall by providing context and creating emotional connections.
• Q: What role does simplicity play in crafting a memorable message?
  A: Simplicity makes a message easier to understand, requiring less cognitive effort and thus making it more likely to be remembered.
• Q: Can non-verbal communication affect how memorable a message is?
  A: Yes, non-verbal cues like body language, facial expressions, and tone of voice can enhance the impact and memorability of a message by making it more believable and engaging.