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Home DisruptiveTECH

Utilizing AI-Powered Contextual Language Models for Enhanced Vocabulary Development in Natural Language Processing

AI systems can be trained on large datasets of text, they may struggle with interpreting context, idiomatic expressions, and subtle linguistic nuances that human language entails, argues Prof. Ojo Emmanuel Ademola

by Techeconomy
August 23, 2024
in DisruptiveTECH
1
Contextual language models
Contextual language models

Contextual language models

UBA
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The field of Artificial Intelligence (AI) has made significant advancements in language processing, thanks to powerful models such as OpenAI’s GPT-3 and Google’s BERT.

These contextual language models have revolutionized natural language understanding and generation, enabling machines to generate human-like text based on the input they receive.

However, the use of such AI systems in language processing can also lead to biases, influenced by the training data they are exposed to and the fine-tuning process for specific tasks.

One issue with AI and vocabulary development is the difficulty in teaching machines to truly understand the nuances and complexities of language. While AI systems can be trained on large datasets of text, they may struggle with interpreting context, idiomatic expressions, and subtle linguistic nuances that human language entails.

Another issue is the lack of cultural and contextual understanding in AI systems, which can lead to biases in language processing. For example, if a language model is trained on predominantly English language text, it may struggle with accurately understanding and translating text in other languages or dialects.

To address these challenges, researchers are exploring new approaches and techniques to improve AI’s vocabulary development. One solution is to incorporate more diverse and representative datasets into training models, which can help AI systems better understand the complexities of language and reduce biases.

Additionally, researchers are working on developing more sophisticated natural language processing algorithms that can better interpret context and semantics in text.

Coherently, improving AI’s vocabulary development requires a multi-faceted approach that includes better training datasets, advanced algorithms, and ongoing research to understand and tackle the complexities of human language.

By continuously pushing the boundaries of AI technology, we can help machines better understand and process language, ultimately leading to more effective and accurate communication between humans and AI systems.

In the context of AI systems training tools for vocabulary development, researchers and developers often utilize a variety of techniques and technologies to enhance language understanding.

One common approach is to use large corpora of text data, such as books, articles, and online sources, to train language models.

For example, tools like OpenAI’s GPT-3 (Generative Pre-trained Transformer 3) are trained on massive amounts of text data to improve their language understanding and generation capabilities.

Additionally, researchers often leverage techniques like word embeddings, which represent words as numerical vectors in a high-dimensional space.

This allows AI systems to capture semantic relationships between words and better understand the meaning of language.

Word2Vec and GloVe are examples of popular word embedding models used in AI training tools for vocabulary development.

Furthermore, researchers are exploring the use of contextual language models, such as BERT (Bidirectional Encoder Representations from Transformers) and ELMo (Embeddings from Language Models), which can better understand the context of words and phrases within a sentence.

These models have significantly improved AI systems’ ability to interpret and generate language accurately.

Modifiable advancements in neural network architectures, such as transformers and recurrent neural networks (RNNs), have played a crucial role in improving AI systems’ language processing capabilities.

These architectures allow AI models to learn complex patterns and relationships in language data, leading to more accurate vocabulary development and understanding.

Consequently, AI systems training tools for vocabulary development leverage a combination of large text datasets, word embeddings, contextual language models, and advanced neural network architectures to enhance language understanding.

By incorporating these tools and techniques into AI development, researchers can continue to push the boundaries of language processing and improve communication between humans and AI systems.

Expansions on Biases in Language Processing:

In the realm of AI systems training tools for vocabulary development, it is crucial to be mindful of the potential biases that can arise in language processing.

One significant issue is the incorporation of biased data in training models, which can perpetuate stereotypes or inequalities in language understanding. For example, if a language model is trained on a dataset that contains biased or offensive language, it may learn and reproduce these biases in its output.

One prominent example of bias in language processing is the case of the Google Translate algorithm, which was found to exhibit gender bias in its translations.

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The algorithm tended to assign gender-specific pronouns based on stereotypical gender roles, reflecting societal biases present in the training data.

This issue highlighted the importance of carefully curating training data to mitigate biases in AI language models.

Furthermore, biases can also emerge in AI systems through the selection of language features and word embeddings. For instance, word embeddings trained on biased text data may capture and reinforce stereotypes or discriminatory language patterns.

Researchers have uncovered instances where word embeddings exhibit racial or gender biases, leading to skewed language interpretations and representations.

Notably, biases can be inadvertently introduced during the design and implementation of AI systems for vocabulary development.

For example, the choice of training data sources, the encoding of language rules, and the selection of evaluation metrics can all contribute to biased language processing outcomes.

Developers need to conduct thorough bias assessments and mitigation strategies throughout the AI model development process.

An example of a contextual language model that can lead to biases in language processing is OpenAI’s GPT-3.

Biases can be introduced into the language generated by GPT-3 through the training data used to pre-train the model.

Similarly, Google’s BERT model is susceptible to biases due to the training data it was exposed to. If the training data includes biased or stereotypical language, these models may inadvertently generate biased or offensive text, impacting the accuracy of language processing tasks.

Furthermore, contextual language models like GPT-3 and BERT can exhibit biases in language processing when fine-tuned on specific datasets for specialized tasks.

For instance, if a company fine-tunes GPT-3 on customer service chat logs containing biased language, the model may produce biased responses during interactions.

This highlights the importance of carefully curating training data, implementing bias mitigation strategies, and rigorous testing to minimize biases in AI language models.

Summarily, biases in language processing can manifest in various forms in AI systems training tools for vocabulary development, posing challenges to the goal of creating fair and inclusive language models.

By acknowledging and addressing these biases through transparent data collection, rigorous evaluation, and bias mitigation techniques, developers can work towards creating more equitable and unbiased AI systems for language understanding.

Conclusively, while contextual language models like GPT-3 and BERT have improved language processing tasks, they also present challenges related to biases.

Addressing biases in AI systems is crucial to ensure fair and unbiased language processing outcomes.

By adopting ethical practices in training data collection, model development, and testing, developers can create more inclusive AI systems that accurately reflect the diversity of human language and communication.

It is essential to continue researching and implementing strategies to mitigate biases in language processing, promoting fairness and equity in AI applications.

[Featured Image Credit]

About the Writer:

*Professor Ojo Emmanuel Ademola is a distinguished academic and digital expert, renowned for his contributions to cybersecurity, information technology management, Artificial Intelligence, Educational and Technological Management and digital economy and governance. Recently inaugurated as the Chairman of the Editorial Board for Triangle News International, Professor Ademola continues to influence the digital and academic landscapes with his profound insights and leadership.

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Tags: BERTContextual language modelsGloVeWord2VecWord2Vec and GloVe
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FG Orders Prosecution to Logical Conclusion of Benjamin Joseph, Alleged Blackmailer of Zinox Chairman The Federal Government has ordered the continuation of prosecution to a logical conclusion of one Benjamin Joseph, owner of Citadel Oracle Concepts Limited, an Ibadan-based ICT retail firm and alleged accuser of the Zinox Chairman, Leo Stan Ekeh, for malicious falsehood over an alleged N170m fraud. https://techeconomy.ng/2020/02/alleged-n170m-firs-contract-complainant-causes-drama-weeps-in-court/ The order was communicated via a letter dated 6th June from the office of the Attorney General of the Federation, Abubakar Malami to the Inspector General of Police, Usman Baba and communicated to the courts by the IGP on 26th September 2022. This was confirmed in a statement by Matthew Burkaa, a Senior Advocate of Nigeria (SAN). According to the statement, Joseph has a previous court judgment of N20m as damages awarded against him by an FCT High Court Abuja, for giving the Federal Government false information after accusing Ekeh of fraudulently converting a contract awarded to his firm by the Federal Inland Revenue Service (FIRS) in 2012. Furthermore, the statement revealed that Joseph is facing another criminal charge for false petitioning before Honourable Justice Peter Kekemeke of the High Court of the FCT, Abuja. https://techeconomy.ng/2022/04/td-africa-vs-benjamin-joseph-why-agf-malami-must-not-soil-his-reputation/ The SAN, who disclosed that this clarification is necessary in informing the public to disregard the various sponsored media reports being circulated online and on social media by Joseph against the Zinox Chairman, also stated that every available legal means will be employed to address the libelous contents in the referenced publications and seek for appropriate remedies and damages, where necessary. The statement reads in part: ‘‘We act for Mr. Leo Stan Ekeh, Technology Distributions Limited (TD) and its staff Chioma Ekeh, Chris Eze Ozims, Oyebode Folashade and Charles Adigwe (hereinafter referred to collectively or individually as “Our Clients”). ‘‘Our Clients have drawn our attention to several online publications, containing some false, distorted and damaging contents in the SAHARA REPORTERS of October 2, 2022 titled: ZINOX GROUP CHAIRMAN, WIFE, 11 OTHERS FACE TRIAL IN NIGERIAN COURT OVER ALLEGED N170M CONTRACT FRAUD NINE YEARS AFTER. A Similar story with the same content was published in OPERA NEWS on 29th September, 2022, and in the NATIONAL WAVES on 29th September 2022 titled: LEO STAN EKEH’S ALLEGED N170.3M FRAUD SCANDAL RESURFACES; and also in THE NEWS MATRICS (Online News Paper Publication) published on the 30th September 2022 titled: FG TO PROSECUTE ZINOX BOSS, EKEH, WIFE OVER ALLEGED N170.3M FRAUD. THE WITNESS (online newspaper) of September 29, 2022, also carried the story. Copies of these online publications have gone viral on social media and have been read globally by different persons and diverse groups, who have been worried by the content of the publication and have continued to bombard our Clients with calls expressing their utter shock and consternation at the content of the publications. ‘‘First of all, of great concern, is how a straightforward business transaction between two corporate entities, Technology Distributions Limited (TD) and Citadel Oracle Concepts Limited has been skewed in a manner to give the erroneous impression that a personal business was transacted by individuals, to wit: Mr. Leo Stan Ekeh, his wife and his named staff with one Mr. Benjamin Joseph. Such personalisation (as carried by the publications) was apparently to achieve an ulterior motive to blackmail, drag, embarrass, and bring down the persons so named in the publication, while the author of the publications appears as a victim and continues to bask in a vain glory.’’ Specifically, Burkaa disclosed that reports of investigation reports by various authorities including the Nigerian Police Force, Special Fraud Unit (SFU) and the Economic and Financial Crimes Commission (EFCC) reveal that Mr. Ekeh and Zinox Technologies Limited are not connected in any way to the allegations that formed the basis of the said libellous publications. ‘‘In fact, in all the investigations by the Nigerian Police and the EFCC, Mr Leo Stan Ekeh, Technology Distributions Limited (TD) and its staff, Mrs. Chioma Ekeh, Mr. Chris Eze Ozims, Mrs. Folashade Oyebode, and Mr. Charles Adigwe have been formally and severally vindicated and absolved of any wrong-doing as the entire allegations were found to be false. On the contrary, the mastermind of all the allegations, a certain Mr. Benjamin Joseph, is presently standing trial in Court for forwarding false allegations via a Petition containing the very allegations that formed the basis of the referenced publications to the Federal Government of Nigeria. That Charge is still pending in Court.’’ Also, he held that neither Mr. Ekeh nor the other persons mentioned in the articles had been served with any charge by the law firm of FALANA & FALANA, as falsely claimed, adding that they only read of the existence of the charge in the media. Burkaa, who condemned the development, described it as going against all known ethics of the administration of justice in Nigeria, especially as the said charge has been widely circulated on print and electronic media with all its details and the full names of persons mentioned along with the charge number. In addition, he stated that the FG has filed a formal charge against Benjamin Joseph for submitting a false petition against Mr. Ekeh, his wife, Mrs. Chioma Ekeh and other persons mentioned in the articles, while noting that the same falsehood has now been reported in those media publications as Burkaa noted that: ‘‘The Criminal Charge will be coming up before His Lordship, the Hon. Justice U.P. Kekemeke of the FCT, High Court, Abuja on the 3rd day of November, 2022 for the defence of Mr. Benjamin Joseph whose “No Case Submission” had been dismissed by the Court, indicating that he has a case to answer. The Federal Government has also written letters through the Director of Public Prosecution of the Federation (DPPF) and the Nigerian Police Force for the continuation of the said prosecution. The letters are dated 6th of June, 2022 and 26th September, 2022. ‘‘It is therefore appalling to our Clients to read, via the above publications, that a Charge had been filed against them by a private law firm associated with Mr. Benjamin Joseph because, they (our Clients) had by a letter dated 19th November, 2018 drawn the attention of the Honourable, the Attorney General of the Federation to the fact that, it was apparent that the Law firm of FALANA &FALANA was acting on the instructions of Mr. Benjamin Joseph, the MD of Citadel Oracle Concepts Limited, who is the Defendant standing trial in Charge No: CR/216/2016. ‘‘More shocking to our Clients is the fact that the Nominal Complainant (Benjamin Joseph) in Charge No: FCT/HC/CR/469/2022 which formed the basis of the above online publications, is the Defendant in Charge No: CR/216/2016 and the subject matter in Charge No: FCT/HC/CR/469/2022 is the very basis for the prosecution of Mr. Benjamin Joseph in Charge No: CR/216/2016. ‘‘It is also imperative to point out that the High Court of the FCT, Per D.Z Senchi J. (as he then was) in Charge No: FCT/HC/CR/244/2018 dismissed as “false petitioning” the very allegations forming the basis of the new charges filed by FALANA & FALANA’S Chambers, and indicted the said Benjamin Joseph for forwarding false information to the Nigerian Police. The court went ahead to slam a fine of N20million against him for writing a Petition containing falsehood against our Clients and to serve as a deterrent to others who might want to mislead security agencies by forwarding false complaints against innocent Nigerians. The said Judgment is dated the 24th day of February, 2021. In fact, Chioma Ekeh and Chris Eze Ozims, who are also supposedly charged in the referred charge, were prosecution witnesses against Benjamin Joseph in the two previously filed charges. So, the present Charge includes the very persons who had been discharged and acquitted on the same set of facts and in whose favour there is a subsisting Judgment.’’ Meanwhile, the SAN added that copies of all the documents mentioned above (including the Judgement, Reports, and letters) are available for verification as they are in various courts’ records, having been tendered in proceedings. The ongoing saga relates to a 2012 Credit Sales of HP Laptops to Citadel Oracle Concepts Limited on an interest-free credit facility when they could not fund the contract awarded to them by FIRS to supply laptops, along with twelve other companies. After FIRS paid all suppliers who were funded by Technology Distribution (TD), the other companies paid TD the pre-agreed invoice value. But Mr. Benjamin Joseph, the MD of Citadel, tried to divert TD’s fund but his partner Princess Kama resisted that move. After TD was paid, a dispute arose between Benjamin Joseph and his partner, Princess Kama, on profit sharing. At a point, Chief Afe Babalola, SAN who was Counsel to Benjamin Joseph, tried to intervene and cause an amicable settlement of the profit-sharing dispute. But Benjamin Joseph wanted the entire money without paying TD. It was at this point that he changed the story and contended that he was not aware of the contract and that his company was used to defraud FIRS. However, during investigation by Nigerian Police and EFCC, the FIRS provided proof that Benjamin Joseph was indeed aware of the contract and that all the ordered computers were fully supplied and received by the FIRS. In addition, Mr. Benjamin Joseph again reported the matter to the Special Fraud Unit (SFU) of the Nigerian Police Force, Milverton Road, Ikoyi. The SFU conducted investigations and indicted him on the basis that a forensic analysis report showed that he signed the board resolution which he alleged was forged. He thereafter lodged another petition to the Police Headquarters, Abuja, and after a thorough investigation, it was found again that his allegations were false. It was on the basis of that finding that he was charged to court in 2016 in Charge No: CR/216/2016 (IGP vs. Benjamin Joseph) for giving false information. That Charge is presently pending before Honourable Justice Peter Kekemeke of the High Court of the FCT, Abuja. Equally important, the Police (Prosecution) has closed their case since 2018 and Mr. Benjamin Joseph has been called upon by the Court to open his defence. Instead of proceeding with the said defense to conclusion, he has devised different tactics in his bid to sway the Attorney General to discontinue the criminal charge preferred against him. Interestingly, the Law Firm of FALANA & FALANA who filed the present charge had earlier in 2018 applied to the Attorney General of the Federation by a letter dated November 1, 2018, for a Fiat to prosecute our clients. In order to convince the office of the Attorney General, Mr. Joseph submitted some spurious reports said to have been made in 2015 and in 2020 by the Nigerian Police, which his solicitors again used to apply for another Fiat. However, the Nigerian Police Headquarters Abuja, by a comprehensive report dated December 1, 2020, discredited and disclaimed all those “reports” relied upon by Mr. Benjamin Joseph, which was used to convince the Attorney General to grant a Fiat in May 2022. On this basis and upon a critical review of all documents relating to the case, the office of the Attorney General saw through the falsehood and issued a new letter to the Police dated 6th June, 2022 directing the Police to continue the prosecution of Benjamin Joseph and bring the criminal charge against him to a logical conclusion. This letter was brought to the attention of the Court by Counsel to the Nigerian Police through their letter dated 26th September, 2022. Burkaa added: ‘‘Mr. Benjamin Joseph and his Legal Team were in Court on 27th September, 2022 and were aware of this directive by the office of the Attorney General. It is therefore appalling that the referenced publications inundated the Press two days after that Court Proceedings with screaming headlines without stating the correct facts for the benefit of the general public.’’ While noting that the publications against the Zinox Chairman were made in bad faith, the SAN contended that they contained false, distorted and slanted narrative to mislead the public, while also stating that they equally contained half-truth carefully skewed to malign and embarrass Mr. Ekeh and hurt his business interests.

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