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Saturday, 14 December 2024

CBN Imposes #150m Fine on Banks Releasing Mint Naira Notes to Hawkers

By Frank Musa
The Central Bank of Nigeria (CBN) has announced that it will slam a fine of 150 million naira per branch on Deposit Money Banks (DMB) nationwide found guilty of facilitating the illegal flow of mint naira notes to currency hawkers and unscrupulous agents.

The apex bank disclosed this in a circular issued on December 13, 2024, signed by the Acting Director of the Currency Operations Department, Mohammed Olayemi.

The circular revealed that the CBN is concerned about the increasing prevalence of mint naira notes being traded by speculators in all corners of the country, a practice the bank described as "impeding efficient and effective cash distribution to customers and the general public".

The circular, which referred to an earlier directive dated November 13, 2024, highlighted the apex bank’s determination to address the commodification of the naira.

Under the directive, any branch of a financial institution found culpable will face a penalty of #150m for the first violation.

Subsequent infractions, the CBN warned, would attract stricter sanctions under the provisions of the Banks and Other Financial Institutions Act (BOFIA) 2020.

To ensure compliance, the apex bank stated that it would increase periodic spot checks in banking halls and Automated Teller Machines (ATMs) while deploying mystery shoppers to uncover illicit cash hawking spots across the country.

It could be recalled the apex bank recently issued a severe warning to the commercial banks across the federation, mandating them to regularly load money on their respective ATMs, or face stiff penalties.

The circular read, “The CBN has noted with dismay the prevalence of illicit flow of mint banknotes to currency hawkers and other unscrupulous economic agents that commodify Naira banknotes, thus impeding efficient and effective cash distribution to banks’ customers and the general public.

“CBN will continue to intensify the periodic spot checks to the banking halls/ATMs to review cash payouts to banks’ customers, as well as mystery shopping to all identified cash hawking spots across the country.

“In this regard, any erring deposit money banks or financial institutions that are culpable of facilitating, aiding, or abetting, by direct actions or inactions, the illicit flow of mint banknotes to currency hawkers and unscrupulous economic agents that commodify Naira banknotes shall be penalised at first instance N150,000,000.00 (One hundred and fifty million Naira) only, per erring branch, and at later instances, apply the full weight of relevant provisions of BOFIA 2020.”

The CBN reminded banks of its ongoing mystery shopping exercises and spot checks aimed at discouraging the abuse of naira notes and ensuring responsible distribution of cash, especially as the festive season approaches.

According to the circular, the initiatives are designed to prevent the flow of newly minted banknotes to hawkers and support efficient cash disbursement to the public.

The mother bank, therefore, warned that any DMB found guilty of releasing cash to unauthorized agents would face financial penalties.

Such banks will be fined 10 per cent of the total value of cash withdrawn from the CBN on the day the offence was committed. Repeat offenders would be fined additional fine of five per cent for subsequent offences.

Microsoft Unveils Phi-4, a Powerful AI Model for Research







Microsoft, a multinational corporation that develops, supports and sells computer software and services, has graciously announced Phi-4, a small yet powerful new generative Artificial Intelligence (AI) model for research preview. 


Phi-4 reportedly comes with 14 billion parameters, and is positioned as a small yet powerful model that is said to ‘excel’ in specialized tasks, particularly mathematical reasoning.


In its released technical report, the tech giant said, “We present phi-4, a 14-billion parameter language model developed with a training recipe that is centrally focused on data quality. Unlike most language models, where pre-training is based primarily on organic data sources such as web content or code, phi-4 strategically incorporates synthetic data throughout the training process. While previous models in the Phi family largely distill the capabilities of a teacher model, specifically GPT-4o.


Phi-4 substantially surpasses its teacher model on STEM-focused QA capabilities, giving evidence that our data-generation and post-training techniques go beyond distillation. Despite minimal changes to the phi-3 architecture, phi-4 achieves strong performance relative to its size– especially on reasoning-focused benchmarks– due to improved data, training curriculum, and innovations in the post-training scheme.” 


Currently, the model is available under a limited release, mostly for research purposes through the company’s Azure AI Foundry platform. It is touted to come with the ability to outperform much larger models, including Google’s Gemini Pro 1.5 and OpenAI’s GPT-4o, on tasks that require complex reasoning. This is evident in the model’s ability to solve mathematical problems, a feature that Microsoft has heavily emphasized in its rollout of Phi-4. 

Presently, larger models like GPT-4 and Gemini Ultra are built with hundreds of billions, or even trillions, of parameters. Phi-4, on the other hand, aims to achieve the results with far fewer computational resources. 


Microsoft attributes Phi-4’s strong performance to the use of “high-quality synthetic datasets” alongside data from human-generated content, while maintaining lower computational costs. 



Phi-4 was trained on synthetic datasets that were specifically crafted to provide diverse, structured problem-solving scenarios. These datasets were supplemented by high-quality human-generated content to ensure that the model encountered a wide range of real-world scenarios during training techniques. 



Once Phi-4 is made available to a wider user base, it could prove to be an eye-opener for mid-sized companies and organizations with limited computing resources. 


By keeping costs significantly lower, when compared to large-scale AI models, Phi-4 can free up resources that can be directed toward other avenues. This could benefit enterprises that have hesitated to adopt AI solutions due to the high resource demands of larger models.

Google Commences Germini 2.0 Flash Experimentation




The Tech giant, Google has announced the launch of Gemini 2.0 Flash and its associated research prototype. It is believes that this is a step forward in the field of Artificial Intelligence (AI) as the new model is designed for developers and showcases several experimental agent-based applications.


Building upon the success of its predecessor, 1.5 Flash, Gemini 2.0 Flash offers enhanced performance with similarly rapid response times. Notably, it outperforms 1.5 Pro on key benchmarks while operating at twice the speed.


Beyond speed improvements, 2.0 Flash introduces new capabilities, including support for multimodal inputs like images, video, and audio, as well as multimodal outputs such as generated images and multilingual text-to-speech audio. It also integrates with external tools like Google Search and code execution environments.


This model is currently available to developers in an experimental phase through the Gemini API in Google AI Studio and Vertex AI, with broader availability planned for January.


Beyond the core model improvements, the announcement highlights the development of AI agents. These agents represent a new approach to interacting with technology, focusing on task completion and proactive assistance. Several research prototypes demonstrate this concept, such as:


  • Project Astra: This project explores the concept of a universal AI assistant capable of understanding multiple languages, utilizing tools like Google Search and Maps, and maintaining context over longer conversations. It has seen improvements in dialogue, tool use, memory, and latency.

  • Project Mariner: This prototype focuses on browser-based agent interaction. It aims to understand and interact with web content, including text, images, and code.

  • Jules: This is an AI-powered code agent designed to assist developers within a GitHub workflow. It can analyze issues, develop plans, and execute code under developer supervision.


  • Gaming Agents: These agents are designed to interact with video games, offering real-time suggestions and utilizing Google Search for game-related information.

  •  There’s also exploration of Gemini 2.0’s spatial reasoning for robotics applications.

A strong emphasis is placed on responsible AI development. The development team is actively addressing safety and security concerns through various measures, including internal reviews, red teaming, safety training, and collaboration with external experts. Specific examples include mitigations against unintentional data sharing in Project Astra and protection against prompt injection in Project Mariner.



The release of Gemini 2.0 Flash and the associated agent prototypes marks an important advancement in AI. The focus on performance, multimodality, and agent-based interaction, combined with a commitment to responsible development, positions Gemini as a key player in the ongoing AI evolution.




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Google Commences Germini 2.0 Flash Experimentation

  The Tech giant, Google has announced the launch of Gemini 2.0 Flash and its associated research prototype. It is believes that this is...

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