Language Model Size Debate Misses the Point: Collaboration, Not Scale, is Key
Steve Mayzak, global managing director for Search AI platform at Elastic, argues that the focus on size in language models is misplaced; instead, the collaborative relationship between specialized (SLMs) and general (LLMs) models should be emphasized, with LLMs acting as 'deciders' that select the a...
Language Model Size Debate Misses the Point: Collaboration, Not Scale, is Key
Steve Mayzak, global managing director for Search AI platform at Elastic, argues that the focus on size in language models is misplaced; instead, the collaborative relationship between specialized (SLMs) and general (LLMs) models should be emphasized, with LLMs acting as 'deciders' that select the a...
Progress
44% Bias Score
Mackenzie Investments' Machine-Learning Driven Stock Strategy Delivers 30% Returns
Arup Datta, senior vice-president at Mackenzie Investments, utilizes a machine-learning model alongside growth, value, and quality metrics to select stocks, resulting in significant returns for the Mackenzie Global Equity Fund, which achieved a 30 percent return over the past year.
Mackenzie Investments' Machine-Learning Driven Stock Strategy Delivers 30% Returns
Arup Datta, senior vice-president at Mackenzie Investments, utilizes a machine-learning model alongside growth, value, and quality metrics to select stocks, resulting in significant returns for the Mackenzie Global Equity Fund, which achieved a 30 percent return over the past year.
Progress
40% Bias Score
AI and Machine Learning Reduce Power Plant Losses
Global electricity transmission and distribution losses average 8ā9%, but some countries experience losses exceeding 20%, impacting sustainable energy development. AI and machine learning offer solutions by optimizing efficiency and reducing losses across the power supply chain, with the global AI-d...
AI and Machine Learning Reduce Power Plant Losses
Global electricity transmission and distribution losses average 8ā9%, but some countries experience losses exceeding 20%, impacting sustainable energy development. AI and machine learning offer solutions by optimizing efficiency and reducing losses across the power supply chain, with the global AI-d...
Progress
36% Bias Score
Santorini Earthquake Swarm Reveals Gaps in Seismic Monitoring
A strong seismic swarm lasting over 20 days near Santorini and Amorgos has spurred a major scientific response using advanced technology, revealing significant shortcomings in the existing seismic monitoring infrastructure and highlighting the importance of open data and machine learning for enhance...
Santorini Earthquake Swarm Reveals Gaps in Seismic Monitoring
A strong seismic swarm lasting over 20 days near Santorini and Amorgos has spurred a major scientific response using advanced technology, revealing significant shortcomings in the existing seismic monitoring infrastructure and highlighting the importance of open data and machine learning for enhance...
Progress
24% Bias Score
AI's Past, Present, and Future: LeCun's Perspective on a New Renaissance
Yann LeCun, in a recent interview, discussed the history of AI research, highlighting a deliberate pause in the 1980s and the current rapid advancements driven by open-source initiatives and self-supervised learning, predicting a future where AI assistants mediate all digital interactions, potential...
AI's Past, Present, and Future: LeCun's Perspective on a New Renaissance
Yann LeCun, in a recent interview, discussed the history of AI research, highlighting a deliberate pause in the 1980s and the current rapid advancements driven by open-source initiatives and self-supervised learning, predicting a future where AI assistants mediate all digital interactions, potential...
Progress
40% Bias Score
Neuro-symbolic AI: Blending Neural Networks and Symbolic Models for Enhanced AI
Neuro-symbolic AI, combining neural networks and symbolic models, offers enhanced prediction and explanation capabilities over traditional AI, addressing limitations in handling subjective events and future trends, as exemplified by its application in B2B marketing and legal fields.
Neuro-symbolic AI: Blending Neural Networks and Symbolic Models for Enhanced AI
Neuro-symbolic AI, combining neural networks and symbolic models, offers enhanced prediction and explanation capabilities over traditional AI, addressing limitations in handling subjective events and future trends, as exemplified by its application in B2B marketing and legal fields.
Progress
56% Bias Score
AI Accelerates Pharmaceutical Drug Development
AI is transforming the pharmaceutical industry by accelerating drug discovery, optimizing clinical trials, and enabling precision medicine, leading to faster, cheaper, and more effective treatments.
AI Accelerates Pharmaceutical Drug Development
AI is transforming the pharmaceutical industry by accelerating drug discovery, optimizing clinical trials, and enabling precision medicine, leading to faster, cheaper, and more effective treatments.
Progress
44% Bias Score
DeepSeek Disrupts AI with Cost-Effective, Open-Source Models
DeepSeek, an open-source AI platform, challenges traditional AI business models with its cost-effective, high-performance models, achieved through innovative techniques like reinforcement learning without human feedback, Mixture-of-Experts design, and low-level hardware optimization, leading to wide...
DeepSeek Disrupts AI with Cost-Effective, Open-Source Models
DeepSeek, an open-source AI platform, challenges traditional AI business models with its cost-effective, high-performance models, achieved through innovative techniques like reinforcement learning without human feedback, Mixture-of-Experts design, and low-level hardware optimization, leading to wide...
Progress
36% Bias Score
AI Agents: Autonomous Action and Real-Time Problem Solving
AI agents, unlike LLMs, autonomously perceive, reason, and act in real-time to achieve goals, marking a significant shift in AI capabilities with both opportunities and challenges for society.
AI Agents: Autonomous Action and Real-Time Problem Solving
AI agents, unlike LLMs, autonomously perceive, reason, and act in real-time to achieve goals, marking a significant shift in AI capabilities with both opportunities and challenges for society.
Progress
36% Bias Score
Accelerated Algorithms Enhance Machine Learning in the Face of Data Explosion
In 2023, the massive volume of data generatedā241 million emails, 4 million Facebook posts, and 360,000 tweets per minuteārequires powerful algorithms like machine learning models for efficient analysis; advancements like Nesterov's method improve speed and efficiency, using variational calculus.
Accelerated Algorithms Enhance Machine Learning in the Face of Data Explosion
In 2023, the massive volume of data generatedā241 million emails, 4 million Facebook posts, and 360,000 tweets per minuteārequires powerful algorithms like machine learning models for efficient analysis; advancements like Nesterov's method improve speed and efficiency, using variational calculus.
Progress
24% Bias Score
Sub-$50 AI Model Achieves Advanced Reasoning Capabilities
Researchers at the Universities of Washington and Stanford trained an AI reasoning model, s1, for under $50 using a distillation technique from Google's Gemini 2.0, achieving performance comparable to OpenAI's o1 and DeepSeek's R1 in math and coding tasks.
Sub-$50 AI Model Achieves Advanced Reasoning Capabilities
Researchers at the Universities of Washington and Stanford trained an AI reasoning model, s1, for under $50 using a distillation technique from Google's Gemini 2.0, achieving performance comparable to OpenAI's o1 and DeepSeek's R1 in math and coding tasks.
Progress
36% Bias Score
Generative vs. Agentic AI: Creating vs. Acting
Generative AI creates content, while agentic AI acts autonomously; their convergence may create AI systems that both create and implement solutions, raising ethical questions.
Generative vs. Agentic AI: Creating vs. Acting
Generative AI creates content, while agentic AI acts autonomously; their convergence may create AI systems that both create and implement solutions, raising ethical questions.
Progress
24% Bias Score