For many years (2023–2025), artificial intelligence has leapt forward across many fronts. Large language models (LLMs) and chatbots, multimodal systems, scientific AI tools, and robotics all saw breakthroughs.

Tech giants released new AI assistants, open-source communities rolled out powerful models, and even regulators moved to address AI’s impact.

Below we survey the most striking achievements, from GPT-4 extensions and Google’s Gemini to AlphaFold’s Nobel Prize and AI-driven discoveries in science and art.

Table of Contents

Generative Language Models and Chatbots

Modern LLMs became vastly more capable and multimodal. OpenAI’s GPT-4 Turbo (announced Nov 2023) can now process 128,000 tokens in one prompt (roughly 300 pages of text) and is much cheaper to run than GPT-4.

In May 2024 OpenAI introduced GPT-4o (Omni), an upgraded model that handles text, images, and audio in real time – effectively giving GPT-4 conversational “vision and hearing”. ChatGPT itself now has built-in image and voice features: users can upload photos or speak to the bot, and it will respond based on that visual or audio input.

  • GPT-4 Turbo and GPT-4o (Omni): GPT-4 Turbo (Nov 2023) lowered costs and extended context length to 128K tokens. GPT-4o (May 2024) made AI truly multimodal, generating text, speech and images interchangeably with near-human speed.
  • ChatGPT advances: By late 2023, ChatGPT “can now see, hear, and speak” – images and audio can be uploaded or spoken as prompts, and the bot can answer accordingly.
    It also integrated DALL·E 3 (Oct 2023) so it can generate images from text with the aid of conversational prompting.
  • Google’s Gemini series: In Dec 2024, Google DeepMind rolled out the first Gemini 2.0 models (“Flash” and prototypes) designed for the “agentic era” – AI that can autonomously carry out multi-step tasks.
    Google has already begun testing Gemini 2.0 in Search (AI Overviews) and other products for over a billion users, reflecting its upgraded reasoning and multimodal abilities.
  • Other models: Meta released LLaMA 3 in April 2024 (open-weight LLMs up to 400B parameters) claiming it outperforms many prior models.
    Anthropic’s Claude 3 and Microsoft’s copilot tools likewise built on these advances (e.g. Copilot built on OpenAI tech).

These innovations let AI assistants hold far longer, richer conversations and handle diverse inputs.

They also power new “assistant” apps via APIs (Google’s “AI Overviews”, OpenAI’s Assistants API, etc.), making AI more accessible to developers and end-users.

Generative Language Models and Chatbots

Multimodal & Creative AI Advances

AI’s creativity and visual understanding have exploded. Text-to-image and text-to-video models reached new heights:

OpenAI’s DALL·E 3 (Oct 2023) generates photorealistic images from prompts and is even integrated with ChatGPT for guided prompt-writing.

Google introduced Imagen 3 (Oct 2024) and Veo 2 (Dec 2024) – state-of-the-art text-to-image and text-to-video engines – which dramatically improve quality, detail, and consistency in AI art and video generation.

Even music AI improved with Google’s MusicFX tools and related research (e.g. MusicLM experiments).

  • Generative art models: DALL·E 3 and Imagen 3 can follow subtle prompts (including embedded text in images) with high fidelity.
    Google’s Veo 2 can generate short video clips from a single text description, a notable step for video synthesis.
    Stable Diffusion and Midjourney have also released newer versions (v3, v6) with better realism this year.
  • AI in devices: Apple launched Apple Intelligence (in iOS 18 and macOS 15, late 2024) – built-in generative AI on iPhone/iPad/Mac.
    It adds writing assistants (rewrite, proofread, summarize in Mail/Pages), an even smarter Siri, and image tools like Image Playground (create fun illustrations via text) and Genmoji (AI-generated custom emoji).
    Photos got natural-language search (“find Maya skateboarding”), and “Clean Up” AI removes unwanted objects from photos.
    Apple’s approach emphasizes on-device processing and privacy.
  • AI in art: A striking example: in Nov 2024 Sotheby’s sold the first painting by a humanoid robot.
    A portrait of Alan Turing drawn by the AI-powered robot Ai-Da fetched US$1.08 million.
    This record-breaking sale (“A.I. God: Portrait of Alan Turing”) underscores AI’s growing role in creativity and its cultural impact.

Overall, generative models are democratizing creativity: anyone can now generate art, music or video with a few words.
The industry focus has shifted from mere novelty (surreal images) to useful image generation (logos, diagrams, maps) and human-like realism.

(In March 2025 OpenAI even released “4o Image Generation”, integrating its best image model into GPT-4o for precise, photorealistic outputs guided by conversation.)

These tools are quickly being woven into apps, browsers, and creative workflows.

Multimodal & Creative AI Advances

AI in Science, Medicine and Math

AI achievements have fueled scientific discovery and research advances:

  • AlphaFold 3 – biomolecules: In Nov 2024 Google DeepMind (with Isomorphic Labs) unveiled AlphaFold 3, a new model that predicts the 3D structures of all biomolecules (proteins, DNA, RNA, ligands, etc.) simultaneously, with unprecedented accuracy.
    For protein-drug interactions, AlphaFold 3 is about 50% more accurate than traditional methods.
    Its creators immediately released a free AlphaFold Server so researchers worldwide can predict molecular structures.
    This expands on AlphaFold 2’s protein-only predictions and is expected to transform drug discovery and genomics research.
  • Nobel Prize – Protein Folding: The importance of this advance was underscored by the 2024 Nobel Prize in Chemistry.
    Demis Hassabis and John Jumper (DeepMind) shared the prize (with David Baker) for developing AlphaFold (protein folding AI).
    The Nobel committee noted AlphaFold “opened up completely new possibilities” in protein design.
    (This is one of the most high-profile AI achievements to date.)
  • AlphaProteo – drug design: Also in 2024, DeepMind announced AlphaProteo, an AI that designs novel protein binders – molecules that bind to target proteins with high strength.
    AlphaProteo can accelerate creation of new antibodies, biosensors and drug leads by generating promising protein structures for specified targets.
  • Mathematics – AlphaGeometry: DeepMind’s AlphaGeometry and AlphaProof proved another breakthrough.
    In July 2024, AlphaGeometry 2 solved a problem from the International Mathematical Olympiad in 19 seconds, reaching the level of a silver medalist.
    This is a rare case of AI tackling advanced high-school math.
  • Quantum computing – AlphaQubit & Willow: AI also improved cutting-edge hardware.
    In 2024 Google announced AlphaQubit, an AI-based decoder that identifies errors in quantum computers (e.g. Google's Sycamore chips) far better than prior methods.
    Then in Dec 2024 Google unveiled Willow, a new quantum chip that, using advanced error correction, solved a benchmark task in under 5 minutes that would take today’s best supercomputer ~10^24 years.
    These gains earned Willow the 2024 “Physics Breakthrough of the Year” award, highlighting AI’s role in quantum progress.

In medicine and health, AI models made strides too. For example, Google’s new Med-Gemini (fine-tuned on medical data) scored 91.1% on a US medical exam benchmark (USMLE-style), beating prior models by a wide margin.

AI-enabled tools for radiology and pathology (e.g. Derm and Path Foundations) were released to improve image analysis.
Overall, AI is now an indispensable research partner – from mapping the human brain at nanoscale (with AI-assisted EM imaging) to accelerating TB screening in Africa, as reported by Google researchers.

AI in Science, Medicine and Math

AI in Robotics and Automation

Robots powered by AI are learning complex real-world tasks.

Tesla’s Optimus humanoid robots were publicly demoed in October 2024 (“We, Robot” event). Several dozen Optimus units walked, stood and even danced on stage – though later reports noted the initial demos were partly remote-controlled by humans.

Still, the event highlighted rapid progress toward general-purpose robots.

  • DeepMind’s ALOHA robots: Google’s AI lab made impressive headway in domestic robots.
    In 2024 the ALOHA robot (Autonomous Legged Household Assistant) learned to tie shoelaces, hang a shirt, repair another robot, insert gears and even clean a kitchen using only AI planning and vision.
    “ALOHA Unleashed” open-sources showed robots coordinating two arms for tasks, a first in general-purpose manipulation.
  • Robotic Transformers: DeepMind introduced RT-2 (Robotic Transformer 2), a vision-language-action model that can learn from both internet images and real robot data.
    RT-2 lets robots interpret instructions like a human would by leveraging web knowledge.
    It was demonstrated helping a robot sort objects by following text commands.
  • Industry robots: Other companies also advanced: Boston Dynamics continued refining Atlas and Spot robots (though no single headline breakthrough), and AI-driven autonomous vehicles improved (Tesla’s Full Self-Driving Beta saw wider rollout, though full autonomy remains unsolved).
    In manufacturing, AI-centric firms like Figure AI raised funds to build household robots for chores.

These efforts show robots doing progressively harder tasks without explicit programming. However, true fully autonomous humanoids are still on the horizon.

The demonstrations (Optimus, ALOHA, RT-2) are milestones, but researchers caution there’s more work before robots can safely and reliably work alongside humans at scale.

AI in Robotics and Automation

AI in Products, Industry and Society

AI’s impact extends to everyday products and even policy:

  • Consumer devices: Major tech products incorporated AI agents.
    Microsoft’s Copilot (embedded in Windows, Office, Bing) and Google’s Bard/Bard AI in Search (Gemini behind it) brought LLM power to users.
    Apple’s devices got Apple Intelligence (as above) and hardware makers like Nvidia sold record numbers of AI GPUs, powering both cloud and consumer AI.
    (Nvidia became the world’s most valuable company in 2024 on the AI boom.)
  • Regulation – EU AI Act: Reflecting AI’s reach, regulators acted too.
    On August 1, 2024 the EU AI Act came into force, the first comprehensive AI law.
    It establishes a risk-based framework: low-risk AI (spam filters, video games) has minimal rules; transparency rules force AI systems like chatbots to disclose they are AI; high-risk AI (medical or hiring tools) faces strict oversight; and clearly unacceptable AI (e.g. “social scoring” of individuals by governments) is banned.
    This set of rules (along with forthcoming guidelines on general-purpose models) is a major achievement in AI governance and is likely to influence standards worldwide.
  • Industry growth: The AI sector itself saw historic funding and valuations: OpenAI reached a reported valuation of $157 billion in late 2023, and companies like Anthropic, Inflection and Chinese AI startups raised multibillion-dollar rounds.
    NVIDIA’s AI hardware demand drove its market cap above $3.5 trillion by mid-2024.
    These numbers underscore how AI has become central to the tech economy.

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AI in Products, Industry and Society

In short, AI is no longer confined to labs or novelty demos – it’s embedded in phones, cars, workplaces and public policy. 

The advancements above – from GPT-4’s vast knowledge to AlphaFold’s scientific revolutions – demonstrate AI’s rapid maturation.

As we head into 2025, these achievements foreshadow even more powerful and practical AI applications in our daily lives.