Editor's Choice


From the editor's desk: A shift towards cost-effective AI infrastructure

28 February 2025 Editor's Choice


Peter Howells, Editor

Soon after US president Donald Trump; announced the Stargate Project offering financial support of $500 billion; towards AI research and development, the world of AI was hit by a bombshell with the announcement of DeepSeek AI model R1. It was designed and built in China by founder Liang&nbspWenfeng, who holds a degree in both Electronic Engineering and Computer Science and is also the current CEO of a hedge fund called High-Flyer. This hedge fund uses AI to analyse financial data to make investment decisions, a process called quantitative trading.

The main reason DeepSeek shook the AI community was by having development costs a fraction of the cost of AI LLMs developed in the USA, despite an import embargo on AI chips that the US imposed on China. AI stocks took a nose-dive after the announcement with company’s involved in AI hardware and software losing as much as 20% of their market value.

Wenfeng was able to perform this miraculous task by stockpiling a huge volume of older generation GPUs over the course of the year and using these to build his AI engine. DeepSeek R1; was released to the public to little fanfare - compared to existing online LLMs – as an opensource AI engine on 20&nbspJanuary&nbsp2025.

Despite being open to the public, many world leaders are sceptical of its intentions, with many countries, including USA and Australia, banning its use on government devices and systems, citing a national security risk.

Another bone of contention came from a well-known AI company, OpenAI, whose ChatGPT app fell to second place on the app store behind DeepSeek AI assistant within days of its release. CEO of OpenAI, Sam&nbspAltman, has accused DeepSeek of using OpenAI’s search results to generate its own responses. In the AI world this is known as ‘knowledge distillation’ or simply ‘distilling’ and is a technique where a large and complex AI model, known as a teacher, transfers its knowledge to a smaller, more efficient student learning model. This allows the student model to perform similar tasks to its bigger brother, while being faster and requiring less computational power [read energy].

Altman has said in a statement that “they believe that a Chinese startup called DeepSeek has used proprietary data from ChatGPT to train their own AI model”. He is essentially accusing them of intellectual property theft. I find the irony of this accusation quite humorous as ChatGPT was initially accused of using proprietary information on the web in its own training, a process that Altman has dismissed as being above board.

However this story may pan out, I believe that the introduction of DeepSeek R1; underscores an industry-wide shift towards more cost-effective AI infrastructure.


Credit(s)



Share this article:
Share via emailShare via LinkedInPrint this page

Further reading:

Four ways to enhance IoT battery performance using emulation software
Concilium Technologies Editor's Choice
Battery life affects the cost and reliability of IoT-based infrastructure and is a key purchasing consideration for consumer electronic IoT devices.

Read more...
NuWave Technologies: Excellence in electronic component procurement
NuWave Technologies Editor's Choice
Based in Randburg, Gauteng, NuWave Technologies is built on core values of integrity, honesty, transparency, and service excellence.

Read more...
Arduino platform with Analog Devices technology for flexible industrial control
Altron Arrow Editor's Choice DSP, Micros & Memory
Software-configurable systems enable industrial OEMs to deliver unprecedented flexibility to the factory floor, while simplifying product complexity.

Read more...
Accelerating RF PCB design in a 5G world
ASIC Design Services Editor's Choice Design Automation
Billions of IoT devices coming online in the coming years will require RF design capabilities that support ultra-fast 5G speeds.

Read more...
Achieving lowest cost, scalable and dynamic wireless mesh network installations
CST Electronics Editor's Choice Telecoms, Datacoms, Wireless, IoT
In many situations it is desirable for sensors to be connected wirelessly in a mesh network as this saves infrastructure and cost since long cabling runs are not required.

Read more...
Residues on PCBs – Causes and remedial measures
Electronic Industry Supplies Editor's Choice Manufacturing / Production Technology, Hardware & Services
Soldering with wire and iron leaves process judgments up to individual operators, and can produce a wide variety of defects, scrap, or long-term quality issues.

Read more...
Improving solder paste printing with squircle aperture designs
Truth Electronic Manufacturing Editor's Choice
The squircle consistently has the highest transfer rate, and comparable or lower variation than when using squares or circles.

Read more...
From the editor's desk: A challenging manufacturing landscape
Technews Publishing News
Electronic manufacturing in South Africa faces many challenges that limit its potential to compete effectively on the global market, with several obstacles that are impeding its development.

Read more...
How AI and ML are enhancing predictive maintenance
Schneider Electric South Africa Editor's Choice Manufacturing / Production Technology, Hardware & Services
The integration of artificial intelligence (AI) and machine learning (ML) is significantly transforming the management of utilities by providing advanced technology that delivers real-time insights into the operational conditions of facilities.

Read more...
3D electronics/additive electronics
Editor's Choice Manufacturing / Production Technology, Hardware & Services
IDTechEx’s report “3D Electronics/Additive Electronics 2024-2034: Technologies, Players, and Markets” analyses the technologies and market trends that promise to bring electronics into the 3D realm.

Read more...